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Due to rapid advancements in robotics technology, mobile robots are now utilized across various industries and applications. Understanding the terrain on which a robot operates can greatly aid its navigation and movement adjustments, ultimately minimizing potential hazards and ensuring seamless operation. This study aims to identify the specific terrain on which a mobile robot travel. Data was gathered using an inertial measurement unit (IMU) installed on the robot for experimental testing. The key contributions of this research are twofold: firstly, the implementation and evaluation of various machine learning techniques using the IMU sensor dataset, comparing their performance using metrics like accuracy, precision, recall, and F1-score. Secondly, after assessing the different techniques, the most effective one is chosen for the final system implementation. Following the experimental evaluation of machine learning techniques, it was determined that the light gradient boosting machine (LGBM) classifier outperformed the others. Consequently, LGBM was utilized for the proposed system's implementation, achieving a 91% accuracy in surface classification. The experimental results highlight the efficiency and viability of the proposed system. [ABSTRACT FROM AUTHOR]

We investigated the ecological validity of an inertial measurement unit (IMU) (Vmaxpro) to assess the movement velocity (MV) during a 1-repetition maximum (1RM) test and for the prediction of load-velocity (L- V) variables, as well as the ecological intra-day and inter-day reliability during free-weight bench press (BP) and squat (SQ). Furthermore, we provide recommendations for the practical use of the sensor. Twenty-three strength-trained men completed an incremental 1RM test, whereas seventeen men further participated in another 3 sessions consisting of 3 repetitions with 4 different loads (30, 50, 70 and 90% of 1RM) to assess validity and intra- and inter-day reliability, respectively. The MV was assessed using the Vmaxpro and a 3D motion capture system (MoCap). L- V variables and the 1RM were calculated based on submaximal velocities. The Vmaxpro showed high validity during the 1RM test for BP (r = 0.935) and SQ (r = 0.900), but with decreasing validity at lower MVs. The L- V variables and the 1RM demonstrated high validity for BP (r = 0.808-0.942) and SQ (r = 0.615-0.741) with a systematic overestimation. Coefficients of variance for intra- and inter-day reliability ranged from 2.4% to 9.7% and from 3.2% to 8.6% for BP and SQ, respectively. The Vmaxpro appears valid at high and moderately valid at low MVs. Depending on the required degree of accuracy, the sensor may be sufficient for the prediction of L- V variables and the 1RM. Our data indicate the sensor to be suitable for monitoring changes in MVs within and between training sessions. [ABSTRACT FROM AUTHOR]

Introduction: Ballet landings produce accelerations that are transmitted proximally up the kinetic chain. If overly excessive/repetitive, these "shocks" to the lower body may contribute to overuse injury. The shocks imposed by different ballet maneuvers are largely unknown at this time, making it difficult to appreciate the physical stresses associated with different maneuvers. Therefore, the purpose of this study was to compare the impact accelerations associated with different common ballet maneuvers. Methods: As part of this study, 11 adolescent ballet dancers performed 9 different common ballet maneuvers: (1) glissade, (2) pas de chat, (3) petit jeté, (4) petit assemblé, (5) grand assemblé, (6) grand jeté, (7) saut de chat, (8) changement, and (9) entrechat quatre. An inertial sensor secured to the pelvis was used to record the peak resultant acceleration during landings ("impact acceleration"). A Friedman test was conducted to compare impact accelerations across the maneuvers and Wilcoxon signed-rank tests were conducted as pairwise comparisons. Results: The omnibus test indicated that there were differences in impact accelerations among the maneuvers (P < .001). In general, the glissade (2.08 ± 0.47g), pes de chat (2.33 ± 0.23g), petit jeté (2.42 ± 0.29g), and petite assemblé (2.54 ± 0.47g) tended to be the lower impact maneuvers; the grand assemblé (2.90 ± 0.41g), grand jeté (2.99 ± 0.33g), and saut de chat (3.13 ± 0.54g) tended to be the more moderate impact maneuvers; and the changement (4.10 ± 0.48g) and entrechat quatre (4.32 ± 0.52g) tended to be higher impact maneuvers. Conclusion: These findings may provide clinicians and dance instructors with greater insight regarding the physical stresses imposed by different ballet maneuvers. [ABSTRACT FROM AUTHOR]

Objective: Unconstrained head motion is necessary to scan for visual cues during navigation, for minimizing threats, and to allow regulation of balance. Following mild traumatic brain injury (mTBI) people may experience alterations in head movement kinematics, which may be pronounced during gait tasks. Gait speed may also be impacted by the need to turn the head while walking in these individuals. The aim of this study was to examine head kinematics during dynamic gait tasks and the interaction between kinematics and gait speed in people with persistent symptoms after mTBI. Setting: A clinical assessment laboratory. Design: A cross-sectional, matched-cohort study. Participants: Forty-five individuals with a history of mTBI and 46 age-matched control individuals. Main Measures: All participants were tested at a single time point and completed the Functional Gait Assessment (FGA) while wearing a suite of body-mounted inertial measurement units (IMUs). Data collected from the IMUs were gait speed, and peak head rotation speed and amplitude in the yaw and pitch planes during the FGA-1, -3, and -4 tasks. Results: Participants with mTBI demonstrated significantly slower head rotations in the yaw (P =.0008) and pitch (P =.002) planes. They also demonstrated significantly reduced amplitude of yaw plane head rotations (P <.0001), but not pitch plane head rotations (P =.84). Participants with mTBI had significantly slower gait speed during normal gait (FGA-1) (P <.001) and experienced a significantly greater percent decrease in gait speed than healthy controls when walking with yaw plane head rotations (FGA-3) (P =.02), but not pitch plane head rotations (FGA-4) (P =.11). Conclusions: Participants with mTBI demonstrated smaller amplitudes and slower speeds of yaw plane head rotations and slower speeds of pitch plane head rotations during gait. Additionally, people with mTBI walked slower during normal gait and demonstrated a greater reduction in gait speed while walking with yaw plane head rotations compared with healthy controls. [ABSTRACT FROM AUTHOR]

Reverse total shoulder arthroplasty (rTSA) is utilized for a variety of indications, but most commonly for patients with rotator cuff arthropathy. This procedure reduces pain, improves satisfaction, and increases clinically measured range of motion (ROM). However, traditional clinical ROM measurements captured via goniometer may not accurately represent 'real-world' utilization of ROM. In contrast, inertial measurement units (IMUs) are useful for establishing ROM outside the clinical setting. We sought to measure 'real-world' ROM after rTSA using IMUs. A previously validated IMU-based method for continuously capturing shoulder elevation was used to assess 10 individuals receiving rTSA (1M, 82 ± 5 years) and compared to a previously captured 10 healthy individuals (4M, 69 ± 20 years) without shoulder dysfunction. Control subject data were previously collected over 1 week of continuous use. Patients undergoing rTSA donned sensors for 1 week pre-rTSA, 6 weeks at 3 months post-rTSA following clearance to perform active-independent ROM, and 1 week at 1 year and 2 years post-rTSA. Shoulder elevation was computed continuously each day. Daily continuous elevation was broken into 5° angle 'bins' (eg, 0-5°, 5-10°, etc.) and converted to percentage of the total day. IMU-based outcome measures were ROM binned percent (as described previously) and maximum/average elevation each week. Clinical goniometric ROM and patient-reported outcome measures were also captured. No differences existed between patient and healthy control demographics. While patients showed improvement in American Shoulder and Elbow Surgeon (ASES) score, pain score, and goniometric ROM, IMU-based average and maximum elevation were equal between control subjects and patients both pre- and post-rTSA. The percent of time spent above 90° was equal between cohorts pre-rTSA, rose significantly at 3 months post-rTSA, and returned to preoperative levels thereafter. Although pain, satisfaction, and ROM measured clinically may improve following rTSA, real-world utilization of improved ROM was not seen herein. Improvements during the acute rehabilitation phase may be transient, indicating longer or more specific rehabilitation protocols are necessary to see chronic improvements in post-rTSA movement patterns. [ABSTRACT FROM AUTHOR]

Problem Statement: Currently, the application for velocity-based training through a 3D Motion Capture System is discarded due to the economic and personal resources involved, being used mainly as laboratory instruments. As an alternative, different device on the market make it possible to assess and control training loads, although not all use the same technology to measure execution velocity. Approach: Specifically, the inertial measurement unit VmaxPro is one of the new additions to the market of sensors based on accelerometry for the control of execution velocity in resistance training and the reliability and validity of this type of device need to be analysed. Purpose: Thus, this study aimed to conduct a concurrent validation for the velocity and range of displacement of the barbell of VmaxPro against a 3D Motion Capture System as the gold standard. The secondary purposes of this study were to analyse the reliability and measurement errors (both random and systematic) of VmaxPro. Results: The main results of the present study are shown in terms of reliability, validity, and accuracy of the VmaxPro. Firstly, the practical device shows excellent to good ICCs values for the reliability of the velocity and range of displacement of the barbell, respectively. Secondly, VmaxPro presents a small underestimation of the velocity of its systematic error (-0.021 m/s) in comparison to the 3D Motion Capture System, contrary to the random error (0.053 m/s), overestimating the velocity measurement, and a measurement errors both systematic and random close to 2 cm for the range of barbell displacement. Finally, VmaxPro presents valid values for both the velocity and range of displacement of the barbell, being a suitable instrument for this purpose. Conclusions: It would be possible for both coaches and athletes to use the inertial measurement unit VmaxPro for the control, monitoring, and evaluation of strength training. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Physical Education Institute / Shanghai Tiyu Xueyuan Xuebao is the property of Editorial Department of Journal of Shanghai University of Sport and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An increased focus on automation in the aerospace industry has led to a demand for flexible manipulators that can achieve high trajectory following accuracy for tasks like machining, joining, and painting. These tasks require an accurate, real-time state estimation of the robot's end-effector. Currently, the most accurate methods of estimating the end-effector state involve using high-end position and orientation sensors such as laser trackers and camera-based metrology systems and tend to focus on accurately estimating the end-effector position and orientation. This paper investigates the potential benefits and practical considerations in supplementing the data from these kinds of sensors with acceleration and angular velocity measurements obtained from an inertial measurement unit (IMU) to improve the overall robot end-effector state estimation including its velocity and angular acceleration. The sensor fusion is achieved using a Kalman Filter for motions with no rotation and using a Particle Filter for motions with rotation. Simulation results indicate that up to 95% improvement in velocity estimation accuracy, and up to 45% improvement in angular acceleration estimation accuracy can be achieved by fusing IMU data with laser tracker data. In addition, the paper analyzes the thresholds of sensor accuracy beyond which fusion no longer provides significant benefits. Finally, hardware experiments are conducted using a fusion of robot encoder data with IMU measurements. These experiments indicate up to 40% improvement in velocity estimation accuracy from the sensor fusion. [ABSTRACT FROM AUTHOR]

This study investigates the use of tibia-mounted inertial measurement units (IMUs) as an alternative to upper trunk-mounted IMUs for assessing lower limb training magnitudes and asymmetries in Badminton players. Cross-Sectional Study. Youth athlete training environment. Thirty-three adolescent Badminton players, grouped based on injury history (non-injured = 19, bilateral = 6, unilateral = 8). Players wore 1 upper trunk-mounted and 2 tibia-mounted IMUs during simulated match-play. Modified vector magnitudes were assessed to identify if the IMUs can discriminate between injury history groups to assess the device location sensitivity, determine to what extent players exhibit movement asymmetry within the sport, and explore if asymmetries exist within groups with injury history. Upper trunk-mounted IMUs could not distinguish between injury history groups. Statistically significant asymmetries were observed in the non-injured group, however these were below the 10% threshold for clinical asymmetry. No significant asymmetries were observed in the bilaterally injured group, while statistically significant asymmetries were observed in the unilaterally injured group, which were above the 10% threshold for clinical asymmetry. These results suggest that direct limb specific IMU measurement offers a method to suitably assess training magnitudes and asymmetry within a sporting performance, rather than isolated non-sport specific testing. • Upper trunk-mounted IMUs could not distinguish athletes based on injury history. • Tibia-mounted IMUs detected significant asymmetries (<10%) in non-injured athletes. • Significant asymmetries (>10%) were detected in unilaterally-injured athletes. • Limb specific IMUs suitable to assess lower limb training magnitudes and asymmetry. [ABSTRACT FROM AUTHOR]

In this paper, the operability of a custombuilt differential drive wheel mobile robot was evaluated using a self-driving algorithm in practical application. Several key parameters need to be realized by the WMR to enable succinct self-driving algorithm evaluations and parameter derivations. The main components of the WMR development were examined in this work, specifically parameter derivations, hardware implementation, steering algorithm and WMR operability. The result obtained indicate that with proper design and careful calibration of sensors, the required driving parameters could be realized. This enables the WMR to potentially serve as data collection platform for future evaluation of self-driving algorithms. [ABSTRACT FROM AUTHOR]

Purpose: Gait evaluation in patients with dizziness is essential during both initial evaluation and vestibular rehabilitation. Inertial measurement unit (IMU)-based gait analysis systems are clinically applicable in patients with dizziness. Since dizzy patients can utilize visual inputs to compensate for vestibular deficits, it is more difficult for them to walk with their eyes closed (EC). In this study, we compared gait characteristics during forward walking with both eyes open (EO) and EC between healthy subjects and dizzy patients. Materials and Methods: Forty-nine healthy controls (mean age 37.18±10.71 years) and 23 patients with dizziness (mean age 49.25± 15.16 years) were subjected to vestibular and gait analyses. Medical histories, physical examinations, and vestibular function tests ruled out possible vestibular deficits in the controls. Subjects were instructed to walk at a comfortable pace for 10 m under two conditions (EO or EC). Spatiotemporal parameters, kinematics, and simulated kinetics of each gait recording were recorded using a shoe-type IMU system and analyzed. Results: Although gait speeds were slower, stride lengths were smaller, and double support times were increased under the EC, compared to the EO condition, in both healthy subjects and dizzy patients, the difference was more prominent in dizzy patients. Phase coordination index values did not differ significantly in either group. Gait asymmetry (GA) increased significantly under the EC condition, compared to the EO condition, in dizzy patients. Conclusion: GA during forward walking was greater in dizzy patients under an EC condition than under an EO condition. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recently, quantitative and repetitive inspections of the old urban area were conducted because many structures exceed their designed lifetime. The health of a building can be validated from the condition of the outer wall, while the slant angle of the wall widely serves as an indicator of urban regeneration projects. Mostly, the inspector directly measures the inclination of the wall or partially uses 3D point measurements using a static light detection and ranging (LiDAR). These approaches are costly, time‐consuming, and only limited space can be measured. Therefore, we propose a mobile mapping system and automatic slant map generation algorithm, configured to capture urban environments online. Additionally, we use the LiDAR‐inertial mapping algorithm to construct raw point clouds with gravity information. The proposed method extracts walls from raw point clouds and measures the slant angle of walls accurately. The generated slant angle map is evaluated in indoor and outdoor environments, and the accuracy is compared with real tiltmeter measurements. [ABSTRACT FROM AUTHOR]

Because nerve injury of muscles around the shoulder can be easily disguised by "trick movements" of the trunk, shoulder dysfunction following brachial plexus injury is difficult to quantify with conventional clinical tools. Thus, to evaluate brachial plexus injury and quantify its biomechanical consequences, we used inertial measurement units, which offer the sensitivity required to measure the trunk's subtle movements. We calculated 6 kinematic scores using inertial measurement units placed on the upper arms and the trunk during 9 functional tasks. We used both statistical and machine learning techniques to compare the bilateral asymmetry of the kinematic scores of 15 affected and 15 able-bodied individuals (controls). Asymmetry indexes from several kinematic scores of the upper arm and trunk showed a significant difference (P <.05) between the affected and control groups. A bagged ensemble of decision trees trained with trunk and upper arm kinematic scores correctly classified all controls. All but 2 patients were also correctly classified. Upper arm scores showed correlation coefficients ranging from 0.55-0.76 with conventional clinical scores. The proposed wearable technology is a sensitive and reliable tool for objective outcome evaluation of brachial plexus injury and its biomechanical consequences. It may be useful in clinical research and practice, especially in large cohorts with multiple follow-ups. [ABSTRACT FROM AUTHOR]

The purpose of this study was to use at-home, portable, continuous monitoring technologies to record arm motion and activity preoperatively and postoperatively after reverse total shoulder arthroplasty (RTSA). Thirty-three patients indicated for RTSA were monitored preoperatively and 3 and 12 months postoperatively. Inertial measurement units were placed on the sternum and upper arm of the operative limb, recording humeral motion relative to the torso for the duration of a waking day. Elevation events per hour (EE/h) > 90°, time spent at >90°, and activity intensity were calculated and compared between time points. Patient-reported outcome measures were also collected at all time points. At 3 (P =.040) and 12 (P =.010) months after RTSA, patients demonstrated a significantly greater number of EE/h > 90° compared with preoperatively. There were no significant differences (P ≥.242) in the amount of time spent at different elevation angles at any time point or in arm activity intensity. Overall, 95% of the day was spent at elevation angles < 60°, and 90% of the day was spent in a low- or moderate-intensity state. Pearson correlations demonstrated relationships between forward elevation and the number of EE/h (r = 0.395, P =.001) and the number of EE/h > 90° (r = 0.493, P <.001). After RTSA, patients significantly increase the frequency of arm elevation to higher angles. However, we found no differences in the amount of time spent at different elevation angles. Overall, after RTSA, >95% of the day was spent at elevation angles < 60° and <1% of the day was spent at >90° of elevation. [ABSTRACT FROM AUTHOR]

To use clinically available inertial measurement units to quantify the control of linear accelerations at the head and trunk during gait in different sensory conditions in individuals with unilateral vestibular loss. Observational study. Outpatient research laboratory. Individuals (n=13; mean age, 47.6±13.7y; 69% women) 6 weeks after vestibular schwannoma resection surgery and vestibular healthy participants (n=16; mean age, 29.7±5.9y; 56% women). Not applicable. Walking speed normalized, root mean square values of cranial-caudal, medial-lateral, and anterior-posterior directed linear accelerations at the head and the trunk while walking in 2 visual sensory conditions (eyes open and eyes closed). Linear mixed models for each root mean square value were fit on the effects of group, condition, and group by condition. The group by condition effect was used to examine the primary hypothesis that individuals with vestibular loss would experience greater change in triplanar root mean square values at the head and trunk from the eyes open to eyes closed condition compared with the vestibular healthy group. The group by condition effect was found to be significant at the head in the cranial-caudal (β=0.39; P =.002), medial-lateral (β=0.41; P <.001), and anterior-posterior (β=0.43; P <.001) directions. The group by condition effect was also significant in the cranial-caudal (β =0.39; P =.002), medial-lateral (β =0.39; P <.001), and anterior-posterior (β =0.23; P =.002) directions at the trunk. Participants who underwent vestibular schwannoma resection were more impaired in their ability to control accelerations at the head and trunk without visual sensory information than vestibular healthy participants. These impairments were detectable using clinically available inertial measurement units. • Control of the head and trunk are impaired after unilateral vestibular loss. • After unilateral vestibular loss, individuals increase reliance on visual information. • Clinical inertial measurement units detect deficits in acceleration control. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is Available in the Text. Background and Purpose: Few tools are currently available to quantify gaze stability retraining exercises. This project examined the utility of a head-worn inertial measurement unit (IMU) to quantify head movement frequency, velocity, and amplitude during gaze stability exercises. Methods: Twenty-eight individuals with multiple sclerosis and complaints of dizziness or a history of falls were randomly assigned to either a strength and aerobic exercise (SAE) or gaze and postural stability (GPS) group. During a 6-week intervention, participants wore a head-mounted IMU 3 times (early, middle, and late). For aim 1, the frequency, mean peak velocity, and mean peak amplitude of head turns during equivalent duration components of group-specific exercises were compared using general linear models. For aim 2, the progression of treatment in the GPS group was examined using general linear regression models for each outcome. Results: Aim 1 revealed the GPS group demonstrated significantly greater velocity and amplitude head turns during treatment than the SAE group. The frequency of head turns did not significantly differ between the 2 groups. The aim 2 analyses demonstrated that the yaw and pitch frequency of head turns significantly increased during gaze stability exercises over the 6-week intervention. Velocity and amplitude of head turns during yaw and pitch gaze stability exercises did not significantly change. Discussion and Conclusions: A head-worn IMU during rehabilitation distinguished between groups. Furthermore, within the GPS group, the IMU quantified the progression of the frequency of head movements during gaze stability exercises over time. Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A320). [ABSTRACT FROM AUTHOR]

Wearable inertial measurement units (IMUs) enable gait analysis in the clinic, but require calibrations that may affect subsequent gait measurements. This study assessed concurrent validity and within-session reliability of gait kinematics measured by a frequently calibrated IMU-based system. Calibration pose accuracy and intra-rater repeatability, and IMU orientation tracking accuracy, were additionally quantified. Calibration poses and gait were recorded in 15 women using IMUs and optical motion capture (OMC) (reference standard) simultaneously. Participants performed six consecutive trials: each comprising a calibration pose and a walk. IMU tracking was assessed separately (once-off) using technical static and dynamic tests. Differences of > 5° constituted clinical significance. Concurrent validity for gait revealed clinically significant between-system differences for sagittal angles (root-mean-square error [RMSE] 6.7°–15.0°; bias −9.3°–3.0°) and hip rotation (RMSE 7.9°; bias −4.2°). After removing modelling offsets, differences for all angles (except hip rotation) were < 5°. Gait curves correlated highly between systems (r > 0.8), except hip rotation, pelvic tilt and -obliquity. Within-session reliability of IMU-measured gait angles was clinically acceptable (standard error of measurement [SEM] < 5°). Calibration poses were repeatable (SEM 0.3°–2.2°). Pose accuracy revealed mean absolute differences (MAD) < 5° for all angles except sagittal ankle, hip and pelvis. IMU tracking accuracy demonstrated RMSE ≤ 2.0°. A frequently calibrated IMU system provides reliable gait measurements; comparing highly to OMC after removing modelling differences. Calibration poses can be implemented accurately for most angles and consistently. IMU-measured gait data are clinically useful and comparable within participants, but should not be compared to OMC-measured data. [ABSTRACT FROM AUTHOR]

Vertical jumps are vital aspects in many sports. Many technologies are available to determine and calculate jump height. One such portable and easy-to-use technology is an Inertial Measurement Unit (IMU) that uses accelerometers, gyroscopes, and magnetometers. The purpose of this study was to compare vertical jump heights calculated from the data captured with an IMU versus true jump height calculated using a gold standard 3-Dimensional Motion Capture system. Ten subjects completed five jumps for six different conditions including vertical counter-movement jumps and jumps involving rotations on the ground and using a trampoline. An average Pearson correlation coefficient of .87 was found between the IMU and motion capture for all conditions. Condition correlations ranged from .76 to .94. Bland-Altman analyses showed that the IMU underestimated the vertical jump height compared to the motion capture by 5.0 to 9.2 cm across all conditions. Results suggest an IMU can be used to measure jump height in a laboratory setting with a reasonable accuracy, even during vertical jumps that include rotations. [ABSTRACT FROM AUTHOR]

This study aimed to (1) figure out the difference in motion smoothness between a nonpathologic shoulder and the other with a rotator cuff tear by measuring the angular velocity using an inertial measurement unit (IMU) sensor and (2) propose the parameters to describe the difference because there is no literature on this topic. We enrolled patients with rotator cuff disease diagnosed by magnetic resonance imaging. The intact shoulder of participants was compared with the shoulder with rotator cuff tear by using IMU on the basis of the parameters that establish motion smoothness: the number of peaks, the peak velocity–to–mean velocity ratio (PV/MV), and the number of sign reversals. In addition, subgroup analysis was performed with respect to tear size (small to medium vs. large to massive). In addition, correlations with the American Shoulder and Elbow Surgeons score and symptom duration (months) were evaluated. Among 24 patients (15 males, 9 females), all 3 parameters for the motion quality of patients with a rotator cuff tear exhibited significant difference. The parameters showed a significant difference between the small to medium tear group and the large to massive tear group. A negative correlation was found between symptom duration and parameters of motion quality, except for PV/MV. Motion quality assessment using IMU showed a marked difference in the shoulder with a rotator cuff tear compared with the intact shoulder. Hence, IMU-based parameters for dynamic motion quality could be considered as an option for assessing the function of the shoulder. [ABSTRACT FROM AUTHOR]

The article discusses the use of wearable inertial sensors effectively quantify arm asymmetry during gait in children with unilateral spastic cerebral palsy. Topics include arm asymmetry increased in running and fast walking support the proof-of-concept that inertial sensors are able to quantify differences between arm movements and capture changes; and broad implications for use in activity tracking and quantifying arm movements in a wide range of real-world activity.

Purpose: This study was intended to explore the continuous changes in the kinematic parameters of hurdlers in a 110 meter (110m) high hurdle race from hurdles 1 through 10. Method: Ten excellent college athletes who specialized in the 110m high hurdle race volunteered for this study. Inertial measurement units (IMUs) strapped to the back of the athlete's feet and 10 high-speed cameras were used to document the movements of the hurdlers as they were hurdling along the entire track. Kwon3D and MATLAB computer programs were employed for the analysis of kinematic parameters (take-off distance, landing distance, take-off distance percentage, landing distance percentage, flight time, time between hurdles, hurdle cycle time, hurdle cycle velocity, height of centre gravity above the hurdle and take-off angles). The trend analysis was introduced to test the changes of the parameters between hurdles. The level of significance was set to α =.05. Results: The results showed that the subjects averaged 14.31±0.29 seconds in their 110m high hurdle tests. Regarding the trend analysis, all kinematic parameters except landing distance displayed quadratic linear patterns along the 110m race. Conclusion: The athletes rapidly gained speed as they sprinted from the starting line and reached their maximum speeds between hurdles 5 and 6, after which their speed declined. In addition, the kinematic parameters changed as the running velocity varied. [ABSTRACT FROM AUTHOR]

Traditional clinical shoulder range-of-motion (ROM) measurement methods (ie, goniometry) have limitations assessing ROM in total shoulder arthroplasty (TSA) patients. Inertial measurement units (IMUs) are superior; however, further work is needed using IMUs to longitudinally assess shoulder ROM before TSA and throughout post-TSA rehabilitation. Accordingly, the study aims were to prospectively capture shoulder elevation in TSA patients and to compare the results with healthy controls. We hypothesized that patients would have reduced maximum elevation before TSA compared with controls but would have improved ROM after TSA. A validated IMU-based shoulder elevation quantification method was used to continuously monitor 10 healthy individuals (4 men and 6 women; mean age, 69 ± 20 years) without shoulder pathology and 10 TSA patients (6 men and 4 women; mean age, 70 ± 8 years). Controls wore IMUs for 1 week. Patients wore IMUs for 1 week before TSA, for 6 weeks at 3 months after TSA, and for 1 week at 1 year after TSA. Shoulder elevation was calculated continuously, broken into 5° angle "bins" (0°-5°, 5°-10°, and so on), and converted to percentages. The main outcome measures were binned movement percentage, maximum elevation, and average elevation. Patient-reported outcome measures and goniometric ROM were also captured. No demographic differences were noted between the cohorts. Average elevation was not different between the cohorts at any time. Control maximum elevation was greater than pre-TSA and post-TSA week 1 and week 2 values. Time under 30° and time above 90° were equal between the cohorts before TSA. After TSA, patients showed decreased time under 30° and increased time above 90°. This study demonstrates that acute and chronic recovery after TSA can be assessed via maximum elevation and time above 90°, respectively. These results inform how healthy individuals and patients use their shoulders before and after TSA. [ABSTRACT FROM AUTHOR]

The trajectory motion of a robot can be a valuable information to estimate the localization of an autonomous robotic system, especially in a very dynamic but structurally-known environments like water pipes where the sensor readings are not reliable. The main focus of this research is to estimate the location of meso-scale robots using a deep-learning-based motion trajectory segment detection system from recorded sensory measurements while the robot travels through a pipe system. The idea is based on the classification of the motion measurements, acquired by inertial measurement unit (IMU), by exploiting the deep learning approach. Proposed idea and utilized methodology are explained in the related sections and it is observed that convolutional neural network approach is quite powerful to overcome the unreliability of IMU data. [ABSTRACT FROM AUTHOR]

Deep Learning has been gaining popularity due to its numerous implementations and continuous growing capabilities, including the prosthetics industry which has trend of evaluation towards the smart operational decision. The aim of this study is to develop a reliable decision-making system for prosthetic hands which is responsible to grasp or point an object located in the interaction area. In order to achieve this goal, we have exploited the measurements taken from a low-cost inertial measurement unit (IMU) and proposed a convolutional neural network-based decision-making system, which utilizes 9 distinct measurement variables as input, 3 axis accelerometer, 3 axis gyroscope and 3 axis magnetometer. The given experiments on this paper successfully identify that the deep learning approach produces reliably 99.2% accuracy on deciding the final prosthetic hand action by analyzing IMU sensor readings that represents motion trajectory of the hand. [ABSTRACT FROM AUTHOR]

Due to the lack of global positioning system (GPS) signals in some enclosed areas, indoor localisation has recently gained significant importance for academics. However, indoor localisation has a number of challenges and defects, including accuracy, cost, coverage, and ease of use. This paper explores the integration between the inertial measurement unit (IMU) and Wi-Fi-based received signal strength indicator (RSSI) measurements, demonstrating their combined potential for robust indoor localisation. IMUs excel at capturing precise short-term motion dynamics, offering insights into an object's acceleration and orientation. Conversely, RSSI measurements serve as valuable indicators for relative positioning within indoor environments. By fusing data from these sources, our approach compensates for the inherent weaknesses of each sensor type. To achieve accurate indoor positioning, we employ techniques such as sensor fusion, Wi-Fi fingerprinting, and dead reckoning. Wi-Fi fingerprinting allows us to create a database that maps RSSI measurements to specific locations, while dead reckoning helps mitigate drift and inaccuracies. By combining these methods, we estimate a device's position with increased precision. Through experimental evaluation, we assess the performance and efficiency of our integrated approach, comparing the estimated path or new location with a predefined reference path. The findings emphasise a significant improvement in accuracy, with the integration of crowd-sensing, particle filtering, and magnetic fingerprinting techniques resulting in a notable increase from 80.49% to 96.32% accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Timed Up and Go test (TUG) is used to assess individual mobility. It evaluates static and dynamic balance by means of the total time required to complete the test, usually measured by a stopwatch. In recent years tools based on portable inertial measurement units (IMU) for clinical application are increasingly available on the market. More specifically, a tool (hardware and dedicated software) to quantify the TUG test based on IMU is now available. However, it has not yet been validated in subjects with Parkinson's disease (PD). Thus, the aim of this study is to compare measurements from instrumented TUG tests (or iTUG) acquired by an IMU with those obtained using an optoelectronic system (the gold standard) and by a stopwatch, to gain an in-depth understanding of IMU behavior in computing iTUG in subjects with PD. To do this, three TUG test trials were carried out on 30 subjects with PD and measured with all three systems simultaneously. System agreements were evaluated using Intraclass Correlation Coefficient and Bland-Altman plots. The device tested showed excellent reliability, accuracy and precision in quantifying total TUG test duration. Since TUG is a widely used test in rehabilitation settings, its automatic quantification through IMUs could potentially improve the quality of assessments in the quantification of PD gait ability. [ABSTRACT FROM AUTHOR]

• A subject-independent attention-based CNN-BiLSTM model was proposed to predict the hip, knee, and ankle joint moment using a single IMU during extensive walking conditions. • Seven configurations of IMUs, including different placement and number of IMUs, were evaluated to explore the influence of IMU setup on the performance of the proposed model. The trade-off between easy-to-use and the optimized accuracy of the prediction model was discussed. • Six previous-published typical deep-learning models were reproduced to compare the performance of the proposed model in predicting joint moments. Better prediction accuracy was achieved using the proposed model. The estimation of lower-limb joint moments during locomotive activities can provide valuable feedback in joint-injury risk evaluation and clinical diagnosis. The use of inertial measurement units (IMUs) in joint moment estimation has drawn considerable attention. Minimizing the number of IMUs deployed on the lower-limb and simplifying the application procedure have long been the pressing problem to be solved during the accurate estimation of multiple joint moments in multiple scenarios. In the present study, the performance of seven different deep-learning models, including the proposed attention-based conventional neural network-bidirectional long short-term memory model and six previous-published typical deep-learning models, were compared in predicting the sagittal plane hip, knee, and ankle joint moments during the most representative locomotive activities. A public dataset was employed to train and validate these models. Seven configurations of IMUs, including different placement and number of IMUs, were evaluated to explore the influence of IMU setup on the performance of the proposed model. Of all seven deep-learning models, best performance was achieved using the proposed model. Pearson correlation coefficient derived from the proposed model using a single IMU attached on the shank, foot, and thigh reached up to 0.85, 0.83 and 0.78, respectively. Shank is the optimal location for attaching a single IMU for the moment prediction of all three joints, while extra IMUs attached elsewhere failed to derive pronounced benefit for improving the estimation accuracy. Thus, even using a single shank-worn IMU, the proposed model is still capable of accurately estimating the joint moments of lower-limbs. [ABSTRACT FROM AUTHOR]

• A subject-independent attention-based CNN-BiLSTM model was proposed to predict the hip, knee, and ankle joint moment using a single IMU during extensive walking conditions. • Seven configurations of IMUs, including different placement and number of IMUs, were evaluated to explore the influence of IMU setup on the performance of the proposed model. The trade-off between easy-to-use and the optimized accuracy of the prediction model was discussed. • Six previous-published typical deep-learning models were reproduced to compare the performance of the proposed model in predicting joint moments. Better prediction accuracy was achieved using the proposed model. The estimation of lower-limb joint moments during locomotive activities can provide valuable feedback in joint-injury risk evaluation and clinical diagnosis. The use of inertial measurement units (IMUs) in joint moment estimation has drawn considerable attention. Minimizing the number of IMUs deployed on the lower-limb and simplifying the application procedure have long been the pressing problem to be solved during the accurate estimation of multiple joint moments in multiple scenarios. In the present study, the performance of seven different deep-learning models, including the proposed attention-based conventional neural network-bidirectional long short-term memory model and six previous-published typical deep-learning models, were compared in predicting the sagittal plane hip, knee, and ankle joint moments during the most representative locomotive activities. A public dataset was employed to train and validate these models. Seven configurations of IMUs, including different placement and number of IMUs, were evaluated to explore the influence of IMU setup on the performance of the proposed model. Of all seven deep-learning models, best performance was achieved using the proposed model. Pearson correlation coefficient derived from the proposed model using a single IMU attached on the shank, foot, and thigh reached up to 0.85, 0.83 and 0.78, respectively. Shank is the optimal location for attaching a single IMU for the moment prediction of all three joints, while extra IMUs attached elsewhere failed to derive pronounced benefit for improving the estimation accuracy. Thus, even using a single shank-worn IMU, the proposed model is still capable of accurately estimating the joint moments of lower-limbs. [ABSTRACT FROM AUTHOR]

Background More and more elderly problems come to our life and the elderly health care become more important. Elderly people with lower extremities weakness usually use walkers to assist in walking. Although the commercial standard walkers (N-type) can improve elderly people's walking ability, users sometimes take risk of falling when using the standard walkers to perform sit-to-stand (STS). The purpose of this study is to design an additional armrest which can be attached to a standard walker for users performing STS more easily and evaluate it with clinical assessments and a body worn sensor. Methods The combination of the walker and the new armrest design are referred to as a better type (B-type). Clinical assessments and a motion analysis were performed on 34 elderly people (age, 83 ± 6 y/o) with a Five Times Sit-to-Stand Test (FTSST), a satisfaction survey and an inertial measurement unit (IMU) attached to the trunk to measure the acceleration data when using B-type and N-type during STS. Results The FTSST result shows that the B-type can reduce about 5 s spending time of elderly people during STS and 63.7% of subjects were more satisfied on the B-type than the N-type. According to the IMU, the result reveals that the B-type can provide subjects higher peak–peak anterio-posterior acceleration, peak flexion acceleration and peak extension acceleration during STS. Conclusion There is a better assistance during STS when using our new armrests design combined with the commercial product which could provide larger acceleration to perform sit-to-stand. [ABSTRACT FROM AUTHOR]

Copyright of Naukovi visti NTUU - KPI is the property of National Technical University of Ukraine KPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Effective horse–rider interactions are a key component of good horse riding regardless of equestrian discipline, but they remain poorly understood in terms of quantifying. The aim of this study was to assess and describe factors of interaction in the rider–horse system at different skill levels for walk, sitting trot, and canter based on the inertial measurement technique. Horse–rider interaction was defined in terms of the time lag of cross-correlation between specific parameters of rider and horse: the smaller the time lag, the better the horse–rider interaction. Ten high level professional riders (PROs) and 10 beginners (BEGs) participated in this study. Based on simultaneous acceleration data and segment angles of rider's segments (pelvis and trunk) and horse's trunk, cross-correlation analysis was used to quantitatively evaluate the interaction for the factors gaits and skill level. The results indicate significant differences in interaction in the various equine gaits. Furthermore, the results of cross-correlation analysis suggest a better horse–rider interaction in roll (sagittal plane) than in pitch (frontal plane), regardless of the investigated skill levels and gaits. However, no significant differences were found between the two examined skill levels after multivariate analysis of variance (Bonferroni post hoc test). The factor skill level showed only statistical tendencies between the interaction of horse's trunk and the rider's pelvis. This study demonstrates the potential of a novel method to determine and characterize the interaction between horse and rider under field conditions. Such quantitative information can be very useful for judges, horsemen, and trainers. [ABSTRACT FROM AUTHOR]

Developing technologies associated with tracking human movement and behaviour enable new applications for competence assessments from training results of professionals, such as medical staff, sportsmen or emergency servicemen. This article considers a methodological approach to design a system for firefighter's skills and competence assessment. Assessed training features such as in-building behaviour and tasks execution are analysed based on data gathered with wireless Ultra-Wideband Real-Time Location System, UWB RTLS, and Inertial Measurement Unit, IMU. The assessment is based on the predefined required training tasks, the expert's expertise and results of the trainee's test. The Unity game engine is used for data processing and visualization. As the comprehensive final map of the trainee's skills, the spider diagram is applied and the single score method provides the conclusive statement. The proposed solution was verified experimentally in real environment. [ABSTRACT FROM AUTHOR]

• The gait signals from 32 FOG patients are collected by the IMU and FSI simultaneously. • Using DNN to extract complementary features from IMU and FSI signals, respectively. • Two different feature fusion schemes are designed and compared. • A multi-modal fusion classifier for FOG monitoring is proposed with an F1-score of 0.943. • A freezing index ratio (FIR) is proposed for automatic labeling of preFOG categories. Freezing of Gait (FOG) is an episodic lower extremity movement disorder that is highly susceptible to falls and carries a serious risk of disability. Monitoring of FOG can assist in the diagnosis and treatment of FOG. Providing appropriate gait guidance along with monitoring can help reduce the frequency and duration of freezing episodes. This study aims to improve the robustness of the monitoring model using multimodal fusion methods. The gait signals from 32 FOG patients are collected by the inertial measurement unit (IMU) and force-sensitive insole (FSI) simultaneously. A multimodal fused FOG monitoring model was constructed by using deep neural networks to extract complementary features from IMU and FSI signals respectively, and feature-level fusion of the two modalities by an adaptive weighting method. Experimental results show that the proposed multimodal fusion approach improves the F1 value by 0.029 in the FOG detection task compared to the unimodal model. In addition, to construct the pre-FOG dataset more accurately, an automatic labeling method of pre-FOG events based on the FOG index ratio is also proposed in this paper. Compared to directly labeling the data 2.5 s before the freezing episode as the pre-FOG event, the proposed labeling method obtained more samples and improved the freezing prediction accuracy by 1.4 %. [ABSTRACT FROM AUTHOR]

Short sprints are important components of most wheelchair court sports, since being faster than the opponent often determines keeping ball possession or not. Sprinting capacity is best measured during a field test, allowing the athlete to freely choose push strategies adapted to their own wheelchair setting, physical ability, classification and speed changes during a sprint. The key test outcome is sprint duration, but there are various ways to accomplish the same sprint time. So can different push strategies be identified in a wheelchair sport and how do they relate to athlete level/classification and wheelchair configuration? These relationships were investigated by field tests of 30 male wheelchair basketball athletes during a 12 meter sprint in their own wheelchair. A recently developed method for ambulatory measurement was used to calculate wheelchair kinematics [1] , providing outcomes on displacement, speed, acceleration and pushes. Additionally maximal isometric push force was recorded and rear seat height was noted. Within the measured athletes, internationals were expected to be faster due to a better physical training status and technique, allowing them to sprint with fewer (but more powerful) pushes. Likewise, athletes of higher classification were expected to be faster due their superior physical capacity, but the effect on the number of pushes used was not that evident. Video analysis was added to validate push detection of the ambulatory measurement system. Mutual correlations and competition level differences of sprint characteristics were calculated. General Linear Models (GLM) were drawn to determine the effect of competition level and classification on sprint time and number of pushes. In the overall dataset sprint characteristics did not correlate significantly with classification, but if split by competition level, there were significant correlations with sprint time (r=-0.715, p=0.006) and number of pushes (r=-0.647, p= 0.017) in the national level athletes. Sprint time, number of pushes and isometric push force differed significantly between national and international level wheelchair basketball athletes. Competition level showed to be a significant (p<0.05) factor in univariate GLMs for sprint time and number of pushes, whereas classification did not. The interaction of competition level and classification as a factor in univariate GLMs was significant. As hypothesized, international level athletes were faster with fewer pushes, even though their higher average seat height was less optimal for propulsion [2] . The interaction effect of competition level and classification in the GLM indicates that the effect of classification on sprint time and number of pushes is different between competition levels. Indeed, in the national level athletes there was a clear relationship between classification and sprint time / number of pushes, but not in internationals. This difference is pointing at a more professional level of wheelchair configuration or better technique of the international athletes regarding sprint performance. Given the correlation between seat height and classification, the seat height of lowly classified athletes seemed optimized for sprinting, whereas seat height of highly classified athletes with already adequate sprinting capacity was optimized for upward reach. Future research based on larger groups with more even distribution over classifications could provide more solid models and reveal more detailed insight in push strategy efficacy. Given the proven reliability of the inertial sensor based method [1] and the proven reliability for push detection in sprinting, this research could well be performed using this easy to use ambulatory method. Although more challenging than well controlled experimental research, the field based setting in this research revealed additional information not only describing the relation between wheelchair setting and performance, but also describing its practical applications if other game demands were taken into account. The results of this approach is believed to assist athletes, coaches and wheelchair experts in decision making concerning wheelchair configuration and athlete training. [ABSTRACT FROM AUTHOR]

Despite almost a century of research, the question of what causes a curling stone to curl (move perpendicular to its initial direction of motion) has no complete answer. Many hypotheses have been formulated, but none has been able to account quantitatively for the full magnitude of the observed curl. The objective of this research was to equip a curling stone with an inertial measurement unit (IMU) and measure its motion, in order to verify a previously published, numerical model of curling stone dynamics. Low cost, small size, accuracy, ease of programming and operation, wireless data communication, and a data-sampling rate near 1 kHz, were selection criteria and constraints for the instrument package. We used the MicroStrain 3DM-GX4-25 system. This is a MEMS-based IMU with a tri-axial gyroscope and a tri-axial linear accelerometer. It was mounted and interfaced with a Bluetooth transmitter, on a curling stone handle. The data were streamed to a host laptop and displayed graphically in real time. Post-processing of the data included filtering and time-integration in order to obtain linear and angular velocities, and displacements. We have compared our experimental results with trajectory data calculated using a previously published numerical model, based on a thermodynamic approach to ice friction. While the observed longitudinal and angular motions are captured reasonably well by the model (errors of about 5% or less), no curl is predicted by the model. [ABSTRACT FROM AUTHOR]

Short sprints are important components of most wheelchair court sports, since being faster than the opponent often determines keeping ball possession or not. Sprinting capacity is best measured during a field test, allowing the athlete to freely choose push strategies adapted to their own wheelchair setting, physical ability, classification and speed changes during a sprint. The key test outcome is sprint duration, but there are various ways to accomplish the same sprint time. So can different push strategies be identified in a wheelchair sport and how do they relate to athlete level/classification and wheelchair configuration? These relationships were investigated by field tests of 30 male wheelchair basketball athletes during a 12 meter sprint in their own wheelchair. A recently developed method for ambulatory measurement was used to calculate wheelchair kinematics [1] , providing outcomes on displacement, speed, acceleration and pushes. Additionally maximal isometric push force was recorded and rear seat height was noted. Within the measured athletes, internationals were expected to be faster due to a better physical training status and technique, allowing them to sprint with fewer (but more powerful) pushes. Likewise, athletes of higher classification were expected to be faster due their superior physical capacity, but the effect on the number of pushes used was not that evident. Video analysis was added to validate push detection of the ambulatory measurement system. Mutual correlations and competition level differences of sprint characteristics were calculated. General Linear Models (GLM) were drawn to determine the effect of competition level and classification on sprint time and number of pushes. In the overall dataset sprint characteristics did not correlate significantly with classification, but if split by competition level, there were significant correlations with sprint time (r=-0.715, p=0.006) and number of pushes (r=-0.647, p= 0.017) in the national level athletes. Sprint time, number of pushes and isometric push force differed significantly between national and international level wheelchair basketball athletes. Competition level showed to be a significant (p<0.05) factor in univariate GLMs for sprint time and number of pushes, whereas classification did not. The interaction of competition level and classification as a factor in univariate GLMs was significant. As hypothesized, international level athletes were faster with fewer pushes, even though their higher average seat height was less optimal for propulsion [2] . The interaction effect of competition level and classification in the GLM indicates that the effect of classification on sprint time and number of pushes is different between competition levels. Indeed, in the national level athletes there was a clear relationship between classification and sprint time / number of pushes, but not in internationals. This difference is pointing at a more professional level of wheelchair configuration or better technique of the international athletes regarding sprint performance. Given the correlation between seat height and classification, the seat height of lowly classified athletes seemed optimized for sprinting, whereas seat height of highly classified athletes with already adequate sprinting capacity was optimized for upward reach. Future research based on larger groups with more even distribution over classifications could provide more solid models and reveal more detailed insight in push strategy efficacy. Given the proven reliability of the inertial sensor based method [1] and the proven reliability for push detection in sprinting, this research could well be performed using this easy to use ambulatory method. Although more challenging than well controlled experimental research, the field based setting in this research revealed additional information not only describing the relation between wheelchair setting and performance, but also describing its practical applications if other game demands were taken into account. The results of this approach is believed to assist athletes, coaches and wheelchair experts in decision making concerning wheelchair configuration and athlete training. [ABSTRACT FROM AUTHOR]

Despite almost a century of research, the question of what causes a curling stone to curl (move perpendicular to its initial direction of motion) has no complete answer. Many hypotheses have been formulated, but none has been able to account quantitatively for the full magnitude of the observed curl. The objective of this research was to equip a curling stone with an inertial measurement unit (IMU) and measure its motion, in order to verify a previously published, numerical model of curling stone dynamics. Low cost, small size, accuracy, ease of programming and operation, wireless data communication, and a data-sampling rate near 1 kHz, were selection criteria and constraints for the instrument package. We used the MicroStrain 3DM-GX4-25 system. This is a MEMS-based IMU with a tri-axial gyroscope and a tri-axial linear accelerometer. It was mounted and interfaced with a Bluetooth transmitter, on a curling stone handle. The data were streamed to a host laptop and displayed graphically in real time. Post-processing of the data included filtering and time-integration in order to obtain linear and angular velocities, and displacements. We have compared our experimental results with trajectory data calculated using a previously published numerical model, based on a thermodynamic approach to ice friction. While the observed longitudinal and angular motions are captured reasonably well by the model (errors of about 5% or less), no curl is predicted by the model. [ABSTRACT FROM AUTHOR]

Equestrians use reins to communicate with the horse. The aim of this study was to describe the amplitudes of rein tension oscillations at canter. Rein tension data were collected from 8 professional riders each riding 2-3 horses during a normal dressage training session using rein tension meters (128 Hz, logged by an inertial measurement unit sensor). Data were stride-split at the maximal positive vertical poll acceleration. Strides were categorized by canter lead, rider position (sitting/2 point), corners, circles, lateral movements, and stride length (collected/working/lengthened). Changes in head angle were determined from gyroscopic sensor data. Dependent data extracted from each stride and rein were maximal tension (MAX), minimal tension (MIN), and the absolute difference between them (CHANGE). Square-root transformed data were analyzed using mixed models with stride categorizations as fixed effects, and rider and horse included as random effects. Findings for rein tension were considered borderline if 0.05< P >0.001, but significant if P < 0.001. For the rider's position, the magnitudes were higher in sitting canter than 2-point seat ( P < 0.0001), except for inside rein MIN value (n = 21,548 strides). For MAX (both reins), MIN (inside), and CHANGE (outside), the right circle had lower values than the left circle or no circle. For the outside rein, MAX and MIN values showed borderline differences with higher values for lengthened strides than working canter ( P = 0.03/0.0014). Inside rein values in right half pass were significantly or borderline higher than left half pass or baseline, and for MIN values, this was found for both inside/outside reins. Both group effects and all pairwise comparisons evaluated were significant for MAX and CHANGE, except the comparison between inside and outside rein in right canter. MAX/MIN tensions were higher if the nose was moving caudally relative to poll at the MAX/MIN event, respectively. Young horses had the largest MAX and CHANGE values, whereas advanced horses had the highest MIN values. The horse contributed 7%, 27%, and 29% of the variation to MIN, MAX, and CHANGE models, respectively. The rider contributed 19% of the variation to the MIN value models but 0% to the MAX and CHANGE models, suggesting that the horse or the dyad (not statistically separable) is responsible for the basic rein tension pattern at canter. Overall results indicate that asymmetry, of riders and/or horses, plays a role in rein tension. [ABSTRACT FROM AUTHOR]

Accurate knowledge of wheelchair kinematics during a match could be a significant factor in performance improvement in wheelchair basketball. To date, most systems for measuring wheelchair kinematics are not suitable for match applications or lack detail in key kinematic outcomes. This study describes the construction of wheel skid correction algorithms when using a three inertial measurement unit (IMUs) configuration for estimating wheelchair kinematics. The reliability of the skid corrected outcomes was assessed in wheelchair basketball match-like conditions. Twenty participants performed a series of tests reflecting different motion aspects of wheelchair basketball. IMU based estimations were compared to the outcomes of a 24-camera optical motion analysis system serving as gold standard. Once the skid correction algorithms were applied, estimation errors were reduced up to 4% of their original magnitude. Calculated Root Mean Square Errors (RMSE) showed good estimates for frame displacement (RMSE≤ 0.05m) and speed (RMSE≤ 0.1m/s) except for three truly vigorous tests. Estimates of horizontal frame rotation (RMSE<3°) and rotational speed (RMSE<7°/s) were very accurate in all conditions. Differences in calculated instantaneous rotation centers (IRC) were small, but somewhat larger in tests performed at high speed (RMSE up to 0.19m). Average test outcomes for linear speed (ICCs > 0.90), rotational speed (ICC>0.99) and IRC (ICC> 0.90) showed high correlations between IMU data and gold standard. Results indicate that wheel skid correction is a prerequisite to reliably measure wheelchair kinematics in sports conditions. Once applied, this method using cheap and affordable sensors, might enable prospective research in wheelchair basketball match conditions and contribute to individual support of athletes in everyday sports practice. [ABSTRACT FROM AUTHOR]

The purpose of this project is to document the design and prototype of a gait analysis device whose function is to actively collect inertial and geometric data of the right leg during human subject locomotion and calculate the dynamic force vectors applied to the mechanical components of the knee articulation due to body mass for use in finite element method analysis. [ABSTRACT FROM AUTHOR]

The aim of this study was to propose a method for full-body movement pattern recognition in climbing, by computing the 3D unitary vector of the four limbs and pelvis during performance. One climber with an intermediate skill level traversed two easy routes of similar rates of difficulty (5c difficulty on French scale), 10m in height under top-rope conditions. The first route was simply designed to allow horizontal edge-hold grasping, while the second route was designed with more complexity to allow both horizontal and vertical edge-hold grasping. Five inertial measurement units (IMUs) were attached to the pelvis, both feet and forearms to analyse the 3D unitary vector of each limb and pelvis. Cluster analysis was performed to detect the number of clusters that emerged from coordination of the four limbs and pelvis during climbing performance. Analysis revealed 22 clusters with 11 clusters unique across the two routes. Six clusters were unique to the simple hold design route and five clusters emerged only in the complex hold design route. We conclude that clustering supported identification of full-body orientations during traversal, representing a level of analysis that can provide useful information for performance monitoring in climbing. [ABSTRACT FROM PUBLISHER]

Abstract: The aim of this study is to compare and validate an Inertial Measurement Unit (IMU) relative to an optic system, and to propose methods for pattern recognition to capture behavioural dynamics during sport performance. IMU validation was conducted by comparing the motions of the two arms of a compass, which was equipped with IMUs and reflective landmarks detected by a multi-camera system. Spearman's rank correlation tests showed good correlations between the IMU and multi-camera system, especially when the angles were normalized. Bland-Altman plot, root mean square and the normalized pairwise variability index showed low differences between the two systems, confirming the good accuracy levels of the IMUs. Regarding pattern recognition, joint angle and limb orientation was respectively studied for 25 m during breaststroke swimming and 10 m of indoor rock climbing in athletes of various skill levels. Pattern recognition was also conducted on a macroscopic parameter that captured inter-limb coordination. IMUs revealed the potential to assess movement and coordination variability between and within individuals from joint angle measures in swimming and limb orientation time-series data in climbing. [Copyright &y& Elsevier]

The unscented Kalman filter (UKF) became very attractive for the navigation sensors data fusion, because of algorithm significant accuracy and implementation advantages. The unscented Kalman filter is based on the unscented transform (UT) to perform the estimation of the system states. The main idea of the unscented transformation is following. It's more effective to approximate probability distribution function than arbitrary transformation or nonlinear function. The developed sensors data fusion algorithm using the UKF is considered in this work. This algorithm was applied for the state estimation of the loosely coupled GPS/INS integrated navigation system. GPS/INS integrated navigation system contains low cost inertial sensors and low cost GPS receiver. To demonstrate the estimation performance, the processing of sensors data was done using linear Kalman filter (KF), extended Kalman filter (EKF) and UKF. As a result, UKF has lower velocity estimation error than EKF during simulated GPS signal outage. [ABSTRACT FROM AUTHOR]

Abstract: Proper pitching mechanics are imperative for developing different types of pitches (e.g., fastball vs. breaking ball) and for preventing injury. Different pitch types are distinguished by the path (i.e. break) and speed of the ball which, in turn, are dictated by the angular velocity of the ball and the velocity of the ball center at the instant of release from the pitcher''s hand. While radar guns effectively measure ball speed, they provide no information about the direction of the velocity of the ball center, the angular velocity of the ball, or the way in which these quantities change during the throw. These quantities can, in principle, be calculated using high-speed video-based motion capture (mocap), but doing so requires measurements in a controlled lab environment taken by a skilled technician. Moreover, mocap is unlikely to accurately resolve the angular velocity of the ball which is crucial to understanding pitching. This paper addresses these shortcomings by presenting an instrumented ball containing a miniature, wireless inertial measurement unit (IMU) to measure ball dynamics on the field of play. Measurements reveal that this technology can deduce the magnitude and direction of the ball''s velocity at release to within 4% when benchmarked against mocap. Moreover, the IMU directly measures the angular velocity of the ball for pitches that remain within the measurement range of the associated angular rate gyros. [Copyright &y& Elsevier]

Abstract: This article discussed the Doppler frequency error effects based on the GPS signal acquisition basic principle. For degrade application environment, one usually will use a longer integration time to complete signal acquisition, which is very inappropriate for LBS. Therefore, we first confirm the actual Doppler frequency contains Gaussian noise term, and then, Initial Doppler frequency was estimated by inertial measurement unit (IMU) and GPS ephemeris, a Auto Regressive (AR) model was used to achieve more accuracy result. After completing above work, a Wavelet Multi-Resolution Analysis (WRMA) was introduced to pre-processing Doppler frequency estimates. Finally, the effectiveness of designed scheme is verified by simulation. The simulation results show that, the Doppler frequency estimation accuracy and code phase estimation speed has greatly improved. It is acceptable to satisfy receiver quick start and frequency error requirements of weak signal tracking. [Copyright &y& Elsevier]

Copyright of Ingenium is the property of Facultad de Ciencias Basicas e Ingenieria de Universidad de San Buenaventura, Revista Ingenium and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)