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A gait training method that can adjust the target leg load is required to meet the varied demands of trainees. In this study, we propose a running training method using a soft gait-assistive suit—a power-assistive device that adds an external force to the leg of a trainee by actuating a pneumatic artificial muscle (PAM). Herein, the assisting force is applied to the leg of the trainee so that muscle activity is reduced throughout the gait cycle. We detected the terminal stance phase as an appropriate assist timing from the pressure information, and the detected timing was used for the PAM control. We conducted a verification experiment of the PAM pressure variation. In a running mode of 7.0 to 10.0 km/h, all data showed that the PAM at the calf front has better detectability than that at the calf back, which is used in conventional detection methods. The experimental results confirmed that the PAM for gait phase detection should be positioned at the calf front during running. The effectiveness of the proposed running training method was verified through experiments on four trainees using a treadmill. The leg electromyogram of the trainees was measured and changes observed. Accordingly, 14 out of 16 channels of the four trainees showed a significant difference, and the electromyograms decreased by the suit assistance in the range of −1.4 to − 80.3% maximum voluntary contraction. Thus, the experimental results quantitatively confirmed that the proposed running assistance method is effective in reducing muscular activity.

Goal: To determine the efficacy of wearable adaptive resistance training for rapidly improving walking ability in children with cerebral palsy (CP). Methods: Six children with spastic CP (five males, one female; mean age 14y 11mo; three hemiplegic, three diplegic; Gross Motor Function Classification System [GMFCS] levels I and II) underwent ten, 20-minute training sessions over four weeks with a wearable adaptive resistance device. Strength, speed, walking efficiency, timed up and go (TUG), and six-minute walk test (6MWT) were used to measure training outcomes. Results: Participants showed increased average plantar flexor strength (17 ± 8%, p = 0.02), increased preferred walking speed on the treadmill (39 ± 25%, p = 0.04), improved metabolic cost of transport (33 ± 9%, p = 0.03), and enhanced performance on the timed up and go (11 ± 9%, p = 0.04) and six-minute walk test (13 ± 9%, p = 0.04). Conclusions: The observed increase in preferred walking speed, reduction in metabolic cost of transport, and improved performance on clinical tests of mobility highlights the potentially transformative nature of this novel therapy; the rate at which this intervention elicited improved function was 3 – 6 times greater than what has been reported previously., Graphical Abstract Resist to restore: A lightweight, untethered ankle exoskeleton device was used to restore strength and improve walking function in six children with cerebral palsy. Ten, 20-minute training session with wearable adaptive resistance, which provided proportional resistance to plantar flexion during the stance phase of gait, led to significant improvements in ankle plantar flexor strength, metabolic cost of transport, and performance on tests of agility and endurance.

Gait retraining to reduce knee loading has been proposed as a conservative treatment option for early-stage knee osteoarthritis. Mounting evidence suggests that a subject-specific approach may be most effective for ensuring consistent knee loading reductions across all individuals within a population. However, it is currently unclear how to determine the required gait modification dosage selection type and amount to both reduce knee loading and satisfy individual preferences. To overcome this challenge, we introduce a novel, mapping-based dosage selection approach to systematically determine multi-parameter gait modifications to reduce knee loading while maintaining individual user preference. In this approach, individuals first explore different dosages of multi-parameter gait modifications, and then a resulting visual map is displayed with a subject-specific dosage selection zone for the target knee loading reduction. Subjects then self-select a preferred gait within their dosage selection zone. To evaluate the feasibility of this approach, fifteen healthy subjects and one knee OA patient performed walking trials on a treadmill involving various dosages of gait modifications to foot progression angle and step width. Subjects quickly selected the subject-specific gait modifications via mapping-based dosage selection during a single 6 min trial, which reduced the knee adduction moment by an average of 14.2%. Resulting subject-specific gait modifications varied, with 6 subjects selecting only toe-in, 5 subjects selecting both toe-in and increased step width, 2 subjects selecting only toe-out, 1 subject selecting both toe-out and increased step width and 1 subject selecting only increased step width. Average perceived exertion was “fairly light” (index was 10.5±2.2). The knee OA patient selected only toe-in and reduced the knee adduction moment by 12.8%. The presented mapping-based dosage selection approach could provide a systematic and practical means to determine subject-specific gait modifications while maintaining individual preferences.

The use of powered ankle-foot prostheses for below-knee amputees leads to challenges like the peak power of the applied actuator and biomechanical features of the prosthesis foot. This paper proposes an efficient powered ankle-foot prosthesis with a series elastic actuator. By combining the geared five-bar spring (GFBS) mechanism and the traditional series elastic actuator (SEA), a series elastic with geared five-bar (SGFB) actuator is built. The new SGFB actuator has the benefits of both the GFBS and the SEA on mimicking biomechanics of the human ankle and reducing the peak power of the motor. The healthy walking gait in the experiment results indicates that the optimized SGFB prosthesis foot including a 150W Maxon DC motor can provide a 70kg subject enough net positive energy with an energy efficiency of 35.3% during normal speed walking in the treadmill trials. The experiment of the SGFB prosthesis foot in semi-active mode shows the advantage on closely mimicking the human biomechanics during the control dorsiflexion phase and the importance of injecting positive energy during the powered plantarflexion phase. The experiment results also show that the optimization of different parameters within the electromechanical model considering the efficiency of the whole drive train can effectively reduce the motor's peak power to 132 W by making the motor more effective in high-power conditions.

When people walk on a treadmill, significant differences exist in postural control if compared to walking on the ground. In this paper, a method combining linear and nonlinear analysis is proposed to evaluate the walking postural control ability. In this method, the movements of the upper body and the feet are analyzed separately, because these parts have more capacity to reflect the characteristics of people’s gait. On this basis, the linear and nonlinear indicators of each part are analyzed, and the postural control ability is evaluated. The method is validated by three healthy subjects walking on both the treadmill and the ground. In treadmill walking case, the results show a smaller upper trunk acceleration (UTa) in the anterior-posterior (AP) direction. In the foot movement analysis, there are significant differences in the performance indexes related to the center of pressure (CoP) when people are walking on the treadmill and the ground. When walking on the treadmill, the velocity, acceleration, and jerk of the CoP in the AP direction are smaller than those in the ground walking case. Besides, when people walk on treadmills at uniform speeds, their feet accelerate is less in the vertical direction, and they have shorter stride length (SL) and longer stride time (ST). These results suggest that people have better postural control when walking on a treadmill. This method can be used as a means of assessing people’s behavior when walking on various situations by evaluating their control posture ability.

In this paper the 2 different approach for anaerobic threshold (AnT) determination and approximation were described. Anaerobic thresholds were calculated for athletes tested on a bicycle ergometer and treadmill ergometer where the heart rate (HR) and pulmonary ventilation parameters (VE), oxygen consumption (VO2) and carbon dioxide expenditure (VCO2) were continuously measured. The first methods for AnT calculations are based on invasive lactate (LA) measurement. For comparison, a non-invasive method based on changing the course of ventilation parameters during exercise is briefly presented. However, the main goal of the paper was the possibility of minimizing the number of blood sampling for lactate measurements from which the lactate curve and anaerobic threshold can be determined. The Matlab program was used to process the calculations. In this paper the 2 different approach for anaerobic threshold (AnT) determination and approximation were described. Anaerobic thresholds were calculated for athletes tested on a bicycle ergometer and treadmill ergometer where the heart rate (HR) and pulmonary ventilation parameters (VE), oxygen consumption (VO2) and carbon dioxide expenditure (VCO2) were continuously measured. The first methods for AnT calculations are based on invasive lactate (LA) measurement. For comparison, a non-invasive method based on changing the course of ventilation parameters during exercise is briefly presented. However, the main goal of the paper was the possibility of minimizing the number of blood sampling for lactate measurements from which the lactate curve and anaerobic threshold can be determined. The Matlab program was used to process the calculations.

In this paper the anaerobic threshold measuring and approximation with minimum number of blood samples is described. Anaerobic thresholds are calculated for athletes tested on a bicycle ergometer and treadmill ergometer where the heart rate and pulmonary ventilation parameters, oxygen consumption and carbon dioxide expenditure are continuously measured. The main goal of the paper is the possibility of minimizing the number of blood sampling for lactate measurements from which the lactate curve and anaerobic threshold can be estimated.

Exercise intensity monitoring of physical activities has drawn increasingly attention as the awareness of the exercise intensity is of great importance for a person to achieve optimal training outcomes. For example, over-training could lead to excessive fatigue and loss of motivation for exercise. Traditional exercise intensity monitoring systems utilize GPS data to track the user’s intensity of cardio activities through his/her position and speed. Such systems however become invalid for indoor exercises on stationary fitness equipments such as the treadmill or exercise bike. Recent work in using body-worn sensors to track the user’s heart rate for exercise intensity monitoring usually involves additional wearable sensors which are only available on some particular fitness equipments, and thus are hard to be used in all occasions. This work presents an exercise intensity monitoring system which is capable of detecting a person’s exercise intensity via smartphones. Our system exploits the off-the-shelf smartphone and its headphone to capture the user’s breathing sound. Given the captured acoustic data, our system performs data pre-processing to remove the environmental noise and identify the non-silent acoustic frames based on the signal energy. Our system then conducts breathing event detection for non-silent frames, and further calibrates the detection results by utilizing the high correlation between breathing cycles to improve the detection accuracy. Moreover, our system can estimate the person’s exercise intensity based on features extracted from the frames which contain breathing sound. Our experiments involving 9 subjects over four-month time period demonstrate that our proposed exercise intensity monitoring system is robust and accurate in both indoor and outdoor environments.

We present a beat-to-beat heart rate tracking algorithm that is designed especially to handle the nonstationary motion artifacts often encountered using photoplethysmographic (PPG) signals acquired from smartwatches or a forehead-worn device, during intense exercise. To date, many algorithms have been based on tracking heart rates during intense exercise using an 8-second average of heart rates, which does not accurately capture the large variation in instantaneous heart rates during exercise. In this paper, we propose a novel technique that can accurately estimate heart rates from wearable PPG signals with subjects running on a treadmill and making other sudden movements. The proposed algorithm includes three parts: 1) time-frequency spectrum estimation of PPG and accelerometer signals, 2) motion artifact removal by subtraction of the time-frequency spectra of the accelerometer signals from the PPG signals, and 3) postprocessing to further reject motion artifact-affected heart rates followed by interpolation of removed heart beats using a cubic spline approach. The proposed approach was compared to one of the recent and most accurate algorithms. The results of the proposed and compared algorithms were evaluated with two datasets (IEEE Signal Processing Cup (N=12) and our own dataset (N=10)) obtained from a smartwatch and a forehead PPG sensor with subjects running on a treadmill. The reference heart rates were obtained from a chest-worn ECG. Our method, using a 12 second windowed segment, resulted in an average absolute error of only 2.94 beats per minute and an average relative error of 2.42 beats per minute, which are a 71% and 94% improvement, respectively, over the compared algorithm.

This paper presents a methodology for the processing of the Photoplethysmography (PPG) signal measured using a smartwatch during motion tests. For statistical validation, signals from 15 healthy subjects have been collected while the subjects are walking on a treadmill. The motion artifacts (MAs) of the PPG signal have been removed demonstrating that the 37% of the signals are affected by MAs. Then, the experimental performance assessment of the PPG signal, from which the heart rate variability (HRV) has been extracted, by measuring the RR intervals, is compared to the RR intervals extracted from ECG signals measured using a multi-parametric chest belt that is considered as a reference sensor. The uncertainty of the PPG sensor in the measurement of the RR intervals is ± 169 ms, (with a coverage factor k = 2) if compared to the reference method, which in percentage is 30%.

Wearable and portable electrocardiographic devices are revolutionizing athlete’s screening through digital health application enabling a continuous monitoring of important cardiac parameters in real-time. Automatic examination of electrocardiogram (ECG) acquired during sport activity is challenging because acquisition conditions often lead to record ECGs with low signal to noise ratio (SNR). The initial issue of automatic ECG analysis is the identification of R peaks. R peaks are fundamental for the estimation of heart rate, which is the primary clinical parameter used by athletes for athletic performance evaluation. Thus, the aim of this research is to propose an R-peak detection algorithm for ECGs acquired during sport activity by portable and wearable sensors dealing with low SNR. The algorithm is based on a noise assisted data analysis method: Ensemble Empirical Mode Decomposition method (EEMD). Localization of R peaks is primarily performed on the first intrinsic mode function extracted by the EEMD. The algorithm was tested on ‘Run on indoor treadmill’ dataset from Physionet. ECGs were acquired during running/light jogging on an indoor treadmill and present a low SNR (1±7 dB). The developed EEMD-based algorithm showed good performances in terms of positive predicted value (91.08%), sensitivity (92.76%), false discovery rate (8.92), false negative rate (7.24%), cumulative statistical index (83.84%) and mean R-peak position error 1.10 [0.46;1.46]ms. EEMD-based algorithm performs efficiently also in computing heart rate. In conclusion, the developed R-peak detection EEMD-based algorithm showed good level of performances even working on low-SNR ECG acquired during sport activity by portable sensors.

The aim of this work was to investigate the use Principal Component Analysis (PCA) applied to signals recorded by 4 textile piezoresistive sensors embedded within a smart garment (SG) to estimate respiratory rate (RR) during walking/running tasks. To this aim, we enrolled 6 subjects who were asked to perform 7 trials on a treadmill at different speeds: one static condition (quiet breathing at rest), three walking trials at 1.6 km/h, 3.0 km/h and 5.0 km/h, and three running trials at 8.0 km/h, 10.0 km/h and 12.0 km/h. We recorded breathing activity using both the SG embedding 4 piezoresistive sensors, located on lower thorax and abdomen, and a reference flowmeter. We estimated RR using three different signals from SG: i) the average along sensors of the band-pass filtered piezoresistive signals (Xbp), the first principal component (P1st) and the average along components of the sub-set of principal components needed to obtain an accounted variance of 0.95 (P95). On the basis of the RR computed with the reference flowmeter, we obtained that, on average, the error committed relying on P95 is 1.02 bpm, the error obtained considering Xbp is 1.04 bpm and the error obtained using P1st is 1.13 bpm. However, the use of P95 allows obtaining a better estimation at high speed tasks than both Xbp and P1st. This finding may suggest that the use of PCA and, specifically, of the signal obtained as the average along all those components required to obtain an accounted variance of 0.95 may be conveniently used to selectively discard breathing-unrelated components, thus improving the estimation of RR.

Brain-Computer Interfaces (BCI) based on motor imagery can be employed to control devices that assist the movement while promoting neuroplasticity. The present paper shows a lower-limb motor imagery BCI that has been designed to control a treadmill and it also considers the level of attention of the subject for limiting the false activations. This BCI works as a state machine in which different classification models were employed depending on the treadmill status during motion or standing. It was tested with three able-bodied subjects and the average performance in closed-loop was 75.6 ±10.3%.

Sports or physical activities most in demand, especially in urban areas, are sports or treadmills. The benefits of a treadmill include increasing muscle strength, improving metabolism, increasing oxygen absorption in the blood, and training the heart and lung muscles. The purpose of this study was to determine the effectiveness of treadmills to increase $VO_{2} Max$ , haemoglobin levels, and erythrocyte index in Medan City non-commissioned officer (NCO) candidates. The population was the non-commissioned officers who trained treadmills at Army Fitness as many as 50 people and sample is limited to 15 people who meet the inclusion requirements. The type of research is quasi-experimental through pre-test and post-test. The technique of analysing data used the SPSS version 22.0 and the test used the Wilcoxon Signed Ranks Test. The results showed that exercise was a treadmill effective in increasing VO 2 Max for non-commissioned officers in Medan City; workouts are treadmill not effective against Haemoglobin levels in non-commissioned officers in Medan City and training treadmill effective against the Erythrocyte Index for Mean Corpuscular Volume (MCV). The research results conclude that exercise is treadmill only effective in increasing VO 2 Max and MCV index values in erythrocytes.

Typical fall sign patterns of the wearer of a wearable walking support device were extracted by walking experiments, and, to realize these typical fall sign patterns, a lower body walking dummy with a dummy cut-off mechanism was developed. The wearable walking support device as the test object is fitted on the walking dummy. This dummy is held in the upright position by a restraint, and made to walk on a treadmill.

In the past two decades, with growing focus of lower limb exoskeleton, large variety of rigid exoskeletons were designed for medical rehabilitation and the other purposes. Compared with the rigid exoskeletons, which added extra inertial to low limb and restricted wearers' movement, the soft wearable lower extremity exoskeleton minimized the impact of these factors on the human body locomotion. In this paper, a novel design of exosuit that provided assistive force for both hip extension and flexion through the variation in hip joint dynamics during strides was proposed. Based on the change of hip moment, an assistance strategy and assistance force curve were came up with. PD type iterative learning control (ILC) method was introduced to reduce the error caused by wearing position and biological characteristics to improve assistance performance. To evaluate assistance performance, the metabolic cost of four subjects wearing exosuit and walking on treadmill at 5km/h in the situations of that without assistance, assisting both hip extension and hip flexion, and assisting hip extension respectively was measured. Compared with assisting hip extension only and wearing exosuit with no assistance, results indicated that the decrease in average net metabolic cost of assisting both hip extension and flexion was 0.445W/kg and 1.027W/kg respectively, corresponding to the average net metabolic cost rate decrease was 7.45% and 15.67%.

Musculoskeletal disorders (MSDs) are very common in people who pursue physiotherapy. Ideally, ergonomics should be taken into consideration in all areas of life, including in the clinic, workplace, and home. Therefore, this study aims to evaluate the optimum posture impact of the kid with cerebral palsy (CP) using the PhyMill product through the DELMIA V5 R20 Rapid Upper Limb Assessment (RULA) analysis. The collection of data started with observation and interviews with the children. Then, the development of the virtual environment for ergonomics analysis is used. The research was conducted in three conditions; sitting on a harness, standing on PhyMill, and walking on PhyMill. As a result, sitting on the harness posture was very dangerous and must be adjusted immediately. The task should be amended in order to resolve the health complications for the children.

Flip-flops are common and popular among Malaysian, considering our hot and humid weather. However, thong-type flip-flops had often been blame as not provide support to lower extremities and thus may cause injury. Therefore the objective of this study is to assess the effect of non-contoured flip-flops during normal walking. Barefoot and flip-flops walking had been tested on 31 volunteers. Kinetic parameters were measured with embedded force plate treadmill, while kinematic parameters were measure using camera recording. Findings show that all different design of thong-type non-contoured flip-flops does not give significant impact on vertical ground reaction force. Walking with flip-flops will significantly increase the step length and stride length, and this decrease the cadence while comparing with barefoot walking. Flip-flops with wider base may help in prevent ankle sprain by significantly reduce the ankle angle during heel strike. The study suggested that flip-flops may not help in reducing the impact of VGRF on lower limb, but may help in reducing the ankle angle and hence prevent the chance of ankle sprain.

An ability of visually-guided and anticipatory adjustments of locomotion corresponding to upcoming obstacles is important to avoid trip-induced fall. For establishing gait training based on visually-guided and anticipatory adjustments, techniques reproducing realistic training environment are essential. Although some previous works proposed virtual obstacles using mixed reality, the feasibility of virtual obstacles encouraging people to perform realistic obstacle negotiation on a treadmill, where gait training is usually conducted, is still unclear. In this study, we investigated toe heights when stepping over the obstacle in both cases of virtual and real obstacles during walking on the treadmill. Five participants stepped over two types of mixed reality boxes and real boxes, with box placements close and distant from them. The results generally indicate that the toe heights of the leading foot tended to be similar between mixed reality and real obstacles in cases where the obstacle was located distant from participants, a condition that enabled participants to predict when obstacles approached. However, the toe heights of the trailing foot tended to be lower when stepping over the MR obstacles than the real obstacles. We discuss the feasibility and shortcomings of the future use of MR HMDs as replacement for traditional gait training setup.

Older adults and people suffering from neurodegenerative disease often experience difficulty controlling gait during locomotion, ultimately increasing their risk of falling. To combat these effects, researchers and clinicians have used metronomes as assistive devices to improve movement timing in hopes of reducing their risk of falling. Historically, researchers in this area have relied on metronomes with isochronous interbeat intervals, which may be problematic because normal healthy gait varies considerably from one step to the next. More recently, researchers have advocated the use of irregular metronomes embedded with statistical properties found in healthy populations. In this paper, we explore the effect of both regular and irregular metronomes on many statistical properties of interstride intervals. Furthermore, we investigate how these properties react to mechanical perturbation in the form of a halted treadmill belt while walking. Our results demonstrate that metronomes that are either isochronous or random metronome break down the inherent structure of healthy gait. Metronomes with statistical properties similar to healthy gait seem to preserve those properties, despite a strong mechanical perturbation. We discuss the future development of this work in the context of networked augmented reality metronome devices., This paper has been accepted for publication by the 18th IEEE Annual Consumer Communications & Networking Conference (CCNC). The copyright is with the IEEE

With the increasing pressure of urban life, people's physical quality shows a significant downward trend. Obesity has become a health "killer" that cannot be ignored in today's society. The popularity of treadmill has become the first choice for people to improve their physical quality and reduce fat and weight in limited space and limited environmental conditions. This paper describes the design process of the treadmill, puts forward the matters needing attention in the design process of the treadmill, and analyzes the rationality of the relationship between the treadmill and the user. In order to design a fitness equipment to meet the needs of family sports, based on the basic modeling of treadmill, combined with the characteristics of home products, the structure of household multifunctional treadmill was designed by using the ergonomic theory of fitness equipment and industrial design knowledge. At the same time, the finite element simulation software is used to analyze the statics of the components of the household multifunctional treadmill. The results show that the structural strength of the home type multifunctional treadmill is qualified. The function integration of fitness equipment and home products can provide reference for the development of family sports fitness equipment.

This paper presents an ECUST Lower-extremity Exoskeleton (ELE-ROBOT) for augmenting human performance. Most exoskeletons calculate joint torques by using ground reaction forces from foot force sensors. However, this method becomes unreliable in the complex terrain environment. We propose a new control strategy by measuring the human-robot interaction forces using force sensors mounted on the wearer’s torso, and placing only switches on the foot. The exoskeleton joint’s torques are estimated by this measured human-robot interaction forces. The experiments were conducted to verify the feasibility of this control method, the wearer carried 35kg load, and walked on the treadmill at 1.3m/s with exoskeleton powered on or off, then the data was compared to the wearer's natural walking gait. The results show ELE-ROBOT can reduce a portion of the carried load that is exerted on the wearer significantly and trace the joints motion in real time.

The ankle is the critical joint between the leg and foot that helps control physical interactions for propulsion, shock absorption, and balance of the body. This paper describes the effect of modulation of ankle impedance via functional electrical stimulation (FES) on balance control in humans while they are in quiet and perturbed stances. Subjects were instructed to stand on a computer-controlled treadmill while their kinematics and foot pressure were measured by an optical motion capture system and a force plate, respectively. The computer-controlled treadmill produced sinusoidal movement, which provided a mechanical perturbation to the subjects. While in quiet and perturbed stances, transcutaneous electrical stimulation with interferential current activated the agonist and antagonist muscles of the tibialis anterior and soleus muscles, which resulted in the co-contraction of the antagonistic ankle muscles. The experimental results show that simultaneous stimulation of the ankle antagonist muscle group using the interferential electrical stimulation (1) increases the root mean square (RMS) of the center of pressure (CoP) while in the quiet stance, and (2) decreases the RMS of the CoP and increases knee movement while in the perturbed stance. These findings highlight the different effects of FES-induced ankle impedance while in quiet and perturbed stances, suggesting that a simple modulation of ankle impedance via FES may not stabilize the postural sway in the quiet stance but rather may disturb it.

Welwalk WW-1000 is a gait exercise robotic assist system that allows subjects to walk on treadmill by attaching a knee-ankle-foot robot to a paralyzed limb. Abnormal gait patterns during exercise using Welwalk WW-1000 are evaluated by gait observation or marker-based motion analysis systems. However, gait observation is a subjective and ordinal measure, and marker-based motion analysis systems are challenging to implement due to the complexity of preparing equipment and attaching markers to subjects. In this study, we propose the Welwalk WW-2000 system, which incorporated a marker-less motion analysis system that detects abnormal gait patterns during exercise using the robotic system. Using this system, it is expected that a gait exercise program can be planned from easily obtainable, objective information. This system detects the features of abnormal gait patterns using the body position coordinates of the subject obtained from three-dimensional, inertial, knee angle, and load sensors. The purpose of this study was to validate the marker-less motion analysis system against marker-based motion analysis systems. One healthy male simulated the seven abnormal gait patterns which occur frequently in stroke patients, with four grades of severity. Spearman"s rank correlation coefficients were calculated for the relationship between the abnormal gait pattern parameters calculated by each motion analysis system. The correlations between the two systems ranged from 0.81 to 0.95. Therefore, it was confirmed that the marker-less motion analysis system of the Welwalk WW-2000 was valid.

Adaptive assistance of gait training robots has been determined to improve gait performance through motion assistance. An important control role during walking is to avoid tripping by controlling minimum toe clearance (MTC), which is an indicator of tripping risk, to avoid its decrease among gait cycles. No conventional gait training robots can adjust assistance timing based on MTC. In this paper, we propose a system that applies force intermittently based on the MTC prediction algorithm to encourage people to avoid lowering the MTC. This prediction algorithm is based on a radial basis function network, the input data of which include the angles, angular velocities, and angular accelerations of the hip, knee, and ankle joints in the sagittal and coronal planes at toe-off. The cable-driven system that can switch between assistance and non-assistance modes applies force when the predicted MTC is lower than the mean value. Nine participants were asked to walk on a treadmill, and we tested the effect of the system. The MTC data before, during, and after the assistance phase were analyzed for 120 s. The results showed that the minimum and first quartile values of MTC could be increased after the assistance phase.

In this work, we propose a method of heart rate estimation by using the infrared thermal images as input. When the heart beats that causes the blood vessels to periodically vasoconstriction and vasodilation, there will be a tiny periodic temperature change on face area. Therefore, the temporal signal from thermal images is considered as the input to our designed DEWNet (DEnseWave Net) CNN model for heart rate estimation. In the experiment, we collected a dataset containing 24 subjects who were running on the treadmill with five different running speeds. Consequently, using this dataset the average error is 13.592 bpm, which shows its feasibility for real-world applications.

In this paper, we analyze fall avoidance strategies with experiments during the applied stimulation of the slipping fall. The objective is a verification whether a fall avoidance movement in a single subject will be changed or not changed by the difference of experimental conditions. There are two conditions in these experiments. One is restrained of subject's movement by a string. The other is increased a intensity of the applying stimulus in experiments. In restrained the condition, caused by limited lowly angle of the shoulder joint and the hip joint, a subject cannot swing a upper limb and a lower limb like a usual in the forward and backward direction. In the condition of the stimulus intensity, caused by control an acceleration of one side belt in split-belt treadmill, a stimulus intensity can be increased or decreased. As a result, in restrained the condition caused by limited lowly angle of the shoulder joint and the hip joint, one subject had fallen in the first half of the trial, but could avoid fall in the latter half of the trial. Therefore, it was found that even if the subject had fallen initially in a condition, the subject may have changed the fall avoidance strategy finally in order to avoid a fall in the same condition.

This paper examines procedure for static and dynamic modeling of oxygen consumption (VO2) and cardiac output (CO) as response to cardiopulmonary exercise on a treadmill ergometer. It should be noted that the derivation of the subject dynamic model was more difficult due to the intermittent load caused by the measurement of lactate. The results are presented on athlete (top football player) who has undergone a total of 10 stress tests over 6 years. The work shows the development of parameters and their modeling by static and dynamic models. The resulting models are generally applicable and the presented procedures can of course also be used for modeling of other physiological parameters. Measurements were performed under laboratory conditions which allowed measurable dosing of the speed and slope of the treadmill and well measurable responses on this load.

We present an automated treadmill featuring physiological-data-driven feedback—PhysioTreadmill, which allows its user to easily control running settings based on their physical condition and can also motivate them through real-time physiological computing. We developed a robust exercise intensity self-adaptive adjustment algorithm using physiological data processing to adjust the user’s physiological state accurately. We also designed exergames with physiological-data-driven visual/audio feedback in PhysioTreadmill. With PhysioTreadmill, we can ideally increase exercise duration, and enhance exercise performance and safety. Two user studies involving 42 participants showed that PhysioTreadmill is user-friendly and can effectively extend users’ training duration.

Immersive virtual reality provides a safe and costeffective approach to administrating balance disruption during ambulation. Previous research has explored the effects of applying continuous perturbations in a virtual environment to challenge balance. This pilot study investigates the ability to disrupt balance with discrete visual perturbations during ambulation in healthy young adults. During the study participants walked on a treadmill within a virtual environment. As they walked the entire visual scene was intermittently shifted to the left or right 1 meter over 1 second. The results demonstrate a significant decrease in step length (p < 0.05) and change in center of mass excursion (p < 0.05) across participants (N=13). Changes in gait lasted up to three steps after application, suggesting a consistent challenge to dynamic balance control as a result of the discrete visual perturbation . Further, participants did not demonstrate a reduction in response to the discrete visual perturbation with repeated exposure. The results indicate that discrete visual perturbations of a virtual scene can be used to challenge gait and modulate center of mass sway. The use of visual perturbations within a virtual environment to challenge dynamic balance could provide a safer and more affordable avenue for balance rehabilitation by reducing the need for systems that physically perturb balance.

The design of effective rehabilitation protocols relies on the ability to accurately assess the physical condition and the rehabilitative needs of the patient. Monitoring muscle fatigue can increase the usability of rehabilitative and restorative devices as it helps avoiding premature tiring and injury of patients whose resistance is already compromised. In this study, we collected EMG and accelerometer data from one healthy subject during a 30-minute walk on treadmill to determine the variations of muscle activation, and gait acceleration patterns, which, however subtle, could be interpreted as early indicators of muscle fatigue. Results show an increasing Tibialis Anterior (TA) and decreasing Soleus (SOL) and Gastrocnemius (GASL, GASM) activation towards the end of the task as compared to the beginning, as well as increasing acceleration peaks during the middle swing phase. By following the approach outlined here we can assess the efficiency and reduction of metabolic cost achieved by an exoskeleton. Furthermore, muscle fatigue may be linked to the efficacy of gait rehabilitation, where decreased muscle fatigue across sessions possibly indicates longer retention of benefits after training and increased walking capacity. This methodology can be used to benchmark novel exoskeletons, monitor fatigue to avoid premature tiring of patients, and optimize rehabilitation therapies.

Ultrasound (US) imaging of muscle has been introduced as a promising sensing modality for assistive device control. Ten able-bodied subjects completed level, incline and decline walking on a treadmill in a motion capture laboratory while wearing reflective markers on upper- and lower-body. A wearable US transducer was affixed to subjects’ anterior thigh, and time-intensity features were extracted from transverse US images of the knee extensor muscles. These features were used to train and test Gaussian process regression models for continuous estimation of knee flexion/extension angular velocity. Four regression models were evaluated: (1) subject-dependent/task-specific, (2) subject-dependent/pooled-tasks, (3) subject-independent/task-specific, and (4) subject-independent/pooled-tasks. Subject-independent models were "tuned" with up to six strides of the test subject’s data to boost performance. A two-factor analysis of variance test was used to assess the effect of each approach on root mean square error (RMSE) of estimated knee angular velocity (α=0.05). Statistical parametric mapping (SPM) was completed to compare actual vs. estimated knee angular velocity as a function of the gait cycle (α=0.05). For incline and level walking, the subject-dependent/pooled-tasks model resulted in the lowest error while the subject-dependent/task-specific model resulted in the lowest error for decline walk. Impressively, the two-factor test revealed no difference between task-specific and pooled-task models. Furthermore, despite capturing many important features of knee velocity across individuals there were, as expected, significant differences between subject-dependent and subject-independent models. Collectively, these results are promising for potential assistive device control with error rates

Increasing physical performance is an urgent task for pharmacology and practical medicine since a decrease in physical performance is a common symptom of many acute and chronic diseases. The aim of this work is to study the effect of monoterpenoid derivatives with 3,7-diazabicyclo [3.3.1] nonane (bispidine) on the physical performance of mice. Physical endurance was studied in two tests: Porsolt forced swimming test with a load of 7% of body weight and running on a treadmill. To assess the effect of the investigated agents on locomotor activity, an open field test was performed. As a result, it was found that, of the two compounds with the codes K1-456 and K1-458, the most effective increase in running and swimming duration is compound K1-458, containing residues of (-) - myrtenal linked to the bispidine moiety through the amino group, at a dose of 100 mg/kg after a single intragastric administration. It was also found that the studied agents statistically significantly increase locomotor activity, distance traveled, speed and reduce the time of the stationary moment when testing in the "open field". Thus, derivatives of bispidine containing monoterpenoid residues are a promising new class of organic compounds for the search for new drugs to increase health.

Under most circumstances, people living in big cities such as Bangkok are concerned with efficient time management and work life balance in compact living spaces such as condominiums and apartments. To maintain an optimal level of fitness given the time constraints and living conditions, people prefer exercising indoors such as indoor cycling, treadmill running, and yoga rather than outdoors such as outdoor running and outdoor biking. Intelligent Fitness Information Ecosystem is an information-rich human fitness activity monitoring environment consisting of exercise equipment and exercise related software modules. We propose an affordable solution for a regular running treadmill to connect and access the ecosystem resources through its communication interface, such treadmill needs additional hardware requirements and software modules to integrate user and activity session data. This new system can be installed on existing treadmill platforms with only minor modifications. This system enables users to keep track (and share) their treadmill exercise experiences.

The role of various types of robot assistance in post-stroke gait rehabilitation has gained much attention in recent years. Furthermore, there is increased popularity to use more than one rehabilitation method in order to utilize the different advantages of each. Naturally, this results in the need to study how the different robot-assisted interventions affect the various underlying sensorimotor mechanisms involved in rehabilitation. To answer this important question, this paper combines a virtual reality experience with a unique robotic rehabilitation device, the Variable Stiffness Treadmill (VST), as a way of understanding interactions across different sensorimotor mechanisms involved in gait. The VST changes the walking surface stiffness in order to simulate real-world compliant surfaces while seamlessly interacting with a virtual environment. Through the manipulated visual and proprioceptive feedback, this paper focuses on the muscle activation patterns before, during, and after surface changes that are both visually informed and uninformed. The results show that there are predictable and repeatable muscle activation patterns both before and after surface stiffness changes, and these patterns are affected by the perceived visual and proprioceptive feedback. The interaction of feedback mechanisms and their effect on evoked muscular activation can be used in future robot-assisted gait therapies, where the intended muscle responses are informed by deterministic models and are tailored to a specific patient’s needs.

Unobtrusive and wearable technologies are gaining broad acceptance in the continuous monitoring of physiological parameters. Among others, the respiratory frequency is increasingly being considered as it allows to detect physiological abnormalities and health status changes, both in clinical and occupational scenarios and in sports science.The respiratory monitoring during physical activity is still challenging because of the artifacts caused by body movements. These breathing-unrelated movements may negatively affect the signal used for respiratory monitoring.This study aimed to investigate the influence of the torso movements that occur during walking and running activities on the signals recorded by a multi-sensor garment. The garment consists of three bands positioned at the level of upper and lower thorax and abdomen. Each band embeds two conductive sensors. The torso movements were recorded by a magneto-inertial measurement unit embedded into the garment.Experimental trials were carried out on four male volunteers during walking and running activities at selected speeds controlled by a treadmill. A flowmeter was used to retrieve reference respiratory frequency values. All the signals were analyzed in the frequency domain to investigate the frequency content.Results show that movements related to the torso rotation (arms and shoulders swing) cause motion artifacts on the garment sensors’ signals. Sensors positioned on the upper thorax and abdomen were found to be much more influenced by breathing-unrelated movements.Despite the influence of the torso movements on the conductive sensors, the garment can provide robust information about the average respiratory rate even during physical activities.

Fall-related injury is a significant health problem on a global scale and is expected to grow with the aging population. Laboratory-based perturbation systems have the capability of simulating various modes of fall-inducing perturbations in a repeatable way. These systems enable fundamental research on human gait and balance and facilitate the development of devices to assist human balance. We present a robotic, rope-driven system capable of rendering bumps and force-fields at a person's pelvis in any direction in the transverse plane with forces up to 200 N, and a 90% rise time of as little as 44 ms, which is faster than a human’s ability to sense and respond to the force. These capabilities enable experiments that require stabilizing or destabilizing subjects as they stand or walk on a treadmill. To facilitate use by researchers from all backgrounds, we designed both a configuration with simpler open-loop force control, and another with higher-performance, closed-loop force control. Both configurations are modular, and the open-loop system is made entirely from 3D-printed and catalog components. The design files and assembly instructions for both are freely available in an online repository.

We design and test a 3 DoF parallel cable system capable of applying precise and accurate impulses to walking and running subjects for the University of Utah’s Treadport Active Wind Tunnel (TPAWT). Using Nexus VICON motion capture and gait algorithms, perturbations can be applied at different points in the subject’s gait. The use of a PID force controller allow the system to create omnidirectional perturbations with walking and running subjects while having the capability to vary amplitude and direction of perturbations. Analysis is presented of the workspace of the large treadmill to test whether the workspace available to activate these perturbations is safe. This paper reports the efficacy of the system and evaluates how warning a runner before impact may affect their displacement. Participants experienced 48 perturbations while running applied with a random combination of a front/back/left/right impact at either toe-off or mid-stance with or without warning. A two sample T-test reveals that warning a runner before impact significantly reduced the magnitude they were displaced for both toe-off (t(46) = 4.98 p

For those with irregular gait, re-calibration of motor control strategies and retraining of coordination are key goals. Thoughtful external forces or resistances during repetitive tasks can reprogram motor control patterns and strategies. Prior work in our lab has utilized this theory to improve gait in various patient groups using the Tethered Pelvic Assist Device (TPAD), a treadmill-based robotic trainer. In this paper, we propose a new, portable extension of the TPAD, which relies on an open-loop, forward kinematics based controller to remove the restriction of walking in the laboratory on a treadmill, and therefore accommodates overground ambulation. To evaluate the effects of this new control scheme and the effects of the users holding the mobile TPAD frame, a dataset of walking in four conditions was collected from eight healthy individuals. When applying a constant pelvic loading force of 10% body weight, the mean ground reaction force increased by 8.2±7.7% when the individual holds the walker frame and 11.1±7.8% when no hand contact is made. The mobile TPAD was shown to still induce a targeted loading on individuals during treadmill walking. The validation of this mobile device’s controller and characterization of holding the frame allow overground studies to be conducted, and now opens the door to new training paradigms for overground gait training.

Various virtual walking systems have been developed using treadmill or leg-support devices to move users’ legs. We proposed and evaluated a virtual walking system for sitting observers using only passive sensations such as optic flow and foot vibrations. In this study, we examined whether the virtual body representing observer’s walking could facilitate the sensations of virtual walking in a virtual environment. We found that the virtual body enhanced sensations of walking, leg action and presence except for self-motion. These results suggest that perception of walking self-body avatar would facilitate sensations of walking and presence independently from foot vibrations.

Indices of variability and stability are essential in evaluating the motions of the human gait. Owing to the inconsistent results of earlier studies, the relationships among popular indices, i.e., maximum Lyapunov exponent (λ), MeanSD, and long-range correlation (α), are inconclusive. In this study, we examined the correlations among these indices using the velocity of the center of body mass for 10 participants walking on a treadmill. In terms of the velocity along the gravitational direction, MeanSD exhibited a negative correlation with the short-term λ S and the long-term λ L when the walking speed was 4.0 km/h. Although a positive correlation between MeanSD and λ is expected based on the meanings of these indices, the present and earlier studies collectively suggest that there is no positive correlation between MeanSD and λ. In the same direction, a positive correlation was found between λ S and α when the walking speed was 3.5 km/h. MeanSD and α tended to exhibit a negative correlation for some conditions, which is reasonable because MeanSD and α indicate the level of variability and the long-term consistency of walking, respectively.