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Recent studies have highlighted the possibility of using surface electromyographic (EMG) signals to develop human–computer interfaces that are also able to recognize complex motor tasks involving the hand as the handwriting of digits. However, the automatic recognition of words from EMG information has not yet been studied. The aim of this study is to investigate the feasibility of using combined forearm and wrist EMG probes for solving the handwriting recognition problem of 30 words with consolidated machine-learning techniques and aggregating state-of-the-art features extracted in the time and frequency domains. Six healthy subjects, three females and three males aged between 25 and 40 years, were recruited for the study. Two tests in pattern recognition were conducted to assess the possibility of classifying fine hand movements through EMG signals. The first test was designed to assess the feasibility of using consolidated myoelectric control technology with shallow machine-learning methods in the field of handwriting detection. The second test was implemented to assess if specific feature extraction schemes can guarantee high performances with limited complexity of the processing pipeline. Among support vector machine, linear discriminant analysis, and K-nearest neighbours (KNN), the last one showed the best classification performances in the 30-word classification problem, with a mean accuracy of 95% and 85% when using all the features and a specific feature set known as TDAR, respectively. The obtained results confirmed the validity of using combined wrist and forearm EMG data for intelligent handwriting recognition through pattern recognition approaches in real scenarios. [ABSTRACT FROM AUTHOR]

Featured Application: Results of this work could be useful in the field of hand gesture recognition based on myoelectric signal processing, which has widespread usage for robotic arms and upper limb prosthesis control. The surface electromyography signal (sEMG) is widely used for gesture characterization; its reliability is strongly connected to the features extracted from sEMG recordings. This study aimed to investigate the use of two complexity measures, i.e., fuzzy entropy (FEn) and permutation entropy (PEn) for hand gesture characterization. Fourteen upper limb movements, sorted into three sets, were collected on ten subjects and the performances of FEn and PEn for gesture descriptions were analyzed for different computational parameters. FEn and PEn were able to properly cluster the expected numbers of gestures, but computational parameters were crucial for ensuring clusters' separability and proper gesture characterization. FEn and PEn were also compared with other eighteen classical time and frequency domain features through the minimum redundancy maximum relevance algorithm and showed the best predictive importance scores in two gesture sets; they also had scores within the subset of the best five features in the remaining one. Further, the classification accuracies of four different feature sets presented remarkable increases when FEn and PEn are included as additional features. Outcomes support the use of FEn and PEn for hand gesture description when computational parameters are properly selected, and they could be useful in supporting the development of robotic arms and prostheses myoelectric control. [ABSTRACT FROM AUTHOR]

In this article, a self-contained procedure to estimate the vertical, medial–lateral, and anterior–posterior displacement of a single sacrum-worn inertial measurement unit (IMU) is presented, which can be related to the human body center of mass (CoM) displacement during treadmill walking through an adaptation of the sacral marker method. Furthermore, a magnetometer-free custom sensor-fusion algorithm for orientation estimation is proposed alongside a practical alignment procedure to refer relative IMU orientation estimation to a ground-fixed reference frame. Twelve healthy subjects performed two trials of treadmill walking at 3, 4, and 5 km/h for 150 s, with a sacrum-worn IMU. Orientation and displacement estimations were then compared with those obtained from an optoelectronic measurement system. Roll, pitch, and yaw angles showed root mean square error (RMSE) lower than 2° for walking trials at 3, 4, and 5 km/h, with Pearson’s correlation coefficient higher than 0.90 for each angle. Displacement accuracy was evaluated in terms of peak-to-trough distances and RMSE. Mean errors resulted lower than 1 mm for each axis of interest and for each gait speed, with RMSE not higher than 2.5 mm. The proposed off-line algorithm can be used in low-budget and infrastructure-free environments, to achieve reliable CoM displacement estimation during cyclic activities such as treadmill walking. [ABSTRACT FROM AUTHOR]

This paper proposes a free dataset, available at the following link, named KIMORE, regarding different rehabilitation exercises collected by a RGB-D sensor. Three data inputs including RGB, depth videos, and skeleton joint positions were recorded during five physical exercises, specific for low back pain and accurately selected by physicians. For each exercise, the dataset also provides a set of features, specifically defined by the physicians, and relevant to describe its scope. These features, validated with respect to a stereophotogrammetric system, can be analyzed to compute a score for the subject’s performance. The dataset also contains an evaluation of the same performance provided by the clinicians, through a clinical questionnaire. The impact of KIMORE has been analyzed by comparing the output obtained by an example of rule and template-based approaches and the clinical score. The dataset presented is intended to be used as a benchmark for human movement assessment in a rehabilitation scenario in order to test the effectiveness and the reliability of different computational approaches. Unlike other existing datasets, the KIMORE merges a large heterogeneous population of 78 subjects, divided into 2 groups with 44 healthy subjects and 34 with motor dysfunctions. It provides the most clinically-relevant features and the clinical score for each exercise. 1 https://univpm-my.sharepoint.com/:f:/g/personal/p008099_staff_univpm_it/EiwbKIzk6N9NoJQx4J8aubIBx0o7tIa1XwclWp1NmRkA-w?e=F3jtBk [ABSTRACT FROM AUTHOR]

The present work proposes an interactive software tool for surface electromyography signal processing and analysis, focused on the assessment of muscular activations during walking and easy-to-use also for users without signal treatment knowledge. The tool is based on two logical steps: first, an automatic detection of muscle activations is provided; then, the user can tune the value of each processing parameter, with a real-time visual feedback. A stride-to-stride evaluation of muscular recruitment and a co-contraction recognition are available, together with the computation of an average myoelectric activation pattern. The tunable signal processing tailors the analysis to any considered application, allowing to extract information from low-quality signals. A muscle activity characterisation from the single stride to the whole walking trial is also provided. Beyond gait analysis and muscles activation timing identification, this tool could be valuable also in an educational scenario, considering the interactive characteristics of the graphical user interface. [ABSTRACT FROM AUTHOR]

The functional reach test (FRT) is widely used for assessing dynamic balance stability in elderly and pathological subjects. Force platforms (FPs) represent a fundamental part of the instrumented FRT experimental setup due to the central role of center-of-pressure (COP) displacement in FRT analysis. Recently, the nintendo wii balance board (NBB) has been suggested as a low-cost and reliable device for ground reaction force and COP measurement in poorly dynamic motor tasks. Therefore, this paper aimed to compare NBB-COP data with those obtained from a laboratory-grade platform during FRT. Data from 48 healthy subjects were simultaneously acquired from both devices. FP-COP and NBB-COP trajectories showed a remarkable correlation in both directions ( ${r}>\textsf {0.990}$ ) and low root-mean-square error values (1.14 ± 0.88 mm and 0.55 ± 0.28 mm for anterior–posterior and medial–lateral direction). Fixed biases between COP-based parameters did not exceed 2% of the FP outcomes with high consistency throughout the present measurement range (ICC consistency always >0.950). Only the COP mean velocity exhibited a tendency toward proportional errors, which can be adjusted by a calibration of NBB data. Findings of this paper confirmed the NBB validity for COP measurement in a widely used motor task as the functional reach, supporting the feasibility of NBB in research scenarios. [ABSTRACT FROM AUTHOR]

Here, the authors present a low cost telerehabilitation system made up of a commercial red-green-blue depth (RGBD) camera and a web-based platform. The authors goal is to monitor and assess subject movement providing acceptable and usable at-home remote rehabilitation services without the presence of a clinician. Clinical goals, defined by physiotherapists, are firstly translated into motion analysis features. A Takagi Sugeno fuzzy inference system (FIS) is then proposed to evaluate and combine these features into scores. In this stage, the 'collaborative design' paradigm is used in depth and complete manner: the contribution of the clinician is not limited only to the rules definition but enters in the core of the evaluation algorithm through the definition of the fuzzy rules. A case study on low back pain rehabilitation involving 40 subjects, 5 exercises, and 4 physiotherapists is then presented to the effectiveness of the proposed system. Results of the validation of the system aimed at the assessment of the reliability of the proposed approach show high correlations between clinician evaluation and FIS scores. In this scenario, due to the high correlation, each FIS could represent a virtual alter-ego of the physiotherapist which enable a real time and free second opinion. [ABSTRACT FROM AUTHOR]

Testing balance through squatting exercise is a central part of many rehabilitation programs and sports and plays also an important role in clinical evaluation of residual motor ability. The assessment of center of pressure (CoP) displacement and its parametrization is commonly used to describe and analyze squat movement and the laboratory-grade force plates (FP) are the gold standard for measuring balance performances from a dynamic view-point. However, the Nintendo Wii Balance Board (NWBB) has been recently proposed as an inexpensive and easily available device for measuring ground reaction force and CoP displacement in standing balance tasks. Thus, this study aimed to compare the NWBB-CoP data with those obtained from a laboratory FP during a dynamic motor task, such as the squat task. CoP data of forty-eight subjects were acquired simultaneously from a NWBB and a FP and the analyses were performed over the descending squatting phase. Outcomes showed a very high correlation ( r ) and limited root-mean-square differences between CoP trajectories in anterior-posterior ( r  > 0.99, 1.63 ± 1.27 mm) and medial-lateral ( r  > 0.98, 1.01 ± 0.75 mm) direction. Spatial parameters computed from CoP displacement and ground reaction force peak presented fixed biases between NWBB and FP. Errors showed a high consistency (standard deviation < 2.4% of the FP outcomes) and a random spread distribution around the mean difference. Mean velocity is the only parameter which exhibited a tendency towards proportional values. Findings of this study suggested the NWBB as a valid device for the assessment and parametrization of CoP displacement during squatting movement. [ABSTRACT FROM AUTHOR]

Background: Heel reconstruction represents a challenge for all plastic surgeons due to the anatomical and functional features of this weight-bearing area. In the last decade a combined use of acellular dermal matrices and skin grafts has been proposed as a reliable and less invasive alternative for complex wound management; nevertheless only a few cases have been reported in the literature. Methods: We describe the long-term outcome of 2 cases of severe degloving trauma of the plantar region with massive soft tissue defects of the foot, that underwent surgical reconstruction with artificial dermis and skin grafts. At the fifth year of follow-up, both patients underwent a clinical and a computerized gait analysis to study their functional outcomes and the kinematics of their gait. Results: Both patients recovered functional ambulation and returned to their own work and vocational activities, showing a symmetric gait and parameters of upright posture fully comparable to normality. Conclusions: Despite the initial concerns about the use of acellular dermal matrices and skin grafts for this kind of injury, they seem to be a simple and safe alternative for weight-bearing reconstruction of the degloved foot. The authors believe that the current study yields useful information and reassurance about their long-term reliability. [ABSTRACT FROM AUTHOR]

Background and Objectives: The use of smartphones can greatly help for gait parameters estimation during daily living, but its accuracy needs a deeper evaluation against a gold standard. The objective of the paper is a step-by-step assessment of smartphone performance in heel strike, step count, step period, and step length estimation. The influence of smartphone placement and orientation on estimation performance is evaluated as well.Methods: This work relies on a smartphone app developed to acquire, process, and store inertial sensor data and rotation matrices about device position. Smartphone alignment was evaluated by expressing the acceleration vector in three reference frames. Two smartphone placements were tested. Three methods for heel strike detection were considered. On the basis of estimated heel strikes, step count is performed, step period is obtained, and the inverted pendulum model is applied for step length estimation. Pearson correlation coefficient, absolute and relative errors, ANOVA, and Bland-Altman limits of agreement were used to compare smartphone estimation with stereophotogrammetry on eleven healthy subjects.Results: High correlations were found between smartphone and stereophotogrammetric measures: up to 0.93 for step count, to 0.99 for heel strike, 0.96 for step period, and 0.92 for step length. Error ranges are comparable to those in the literature. Smartphone placement did not affect the performance. The major influence of acceleration reference frames and heel strike detection method was found in step count.Conclusion: This study provides detailed information about expected accuracy when smartphone is used as a gait monitoring tool. The obtained results encourage real life applications. [ABSTRACT FROM AUTHOR]

Background: In this paper, squat named by Authors unconstrained because performed without constrains related to feet position, speed, knee maximum angle to be reached, was tested as motor task revealing differences in functional performance after knee arthroplasty. It involves large joints ranges of motion, does not compromise joint safety and requires accurate control strategies to maintain balance. Methods: Motion capture techniques were used to study squat on a healthy control group (CTR) and on three groups, each characterised by a specific knee arthroplasty design: a Total Knee Arthroplasty (TKA), a Mobile Bearing and a Fixed Bearing Unicompartmental Knee Arthroplasty (respectively MBUA and FBUA). Squat was analysed during descent, maintenance and ascent phase and described by speed, angular kinematics of lower and upper body, the Center of Pressure (CoP) trajectory and muscle activation timing of quadriceps and biceps femoris. Results: Compared to CTR, for TKA and MBUA knee maximum flexion was lower, vertical speed during descent and ascent reduced and the duration of whole movement was longer. CoP mean distance was higher for all arthroplasty groups during descent as higher was, CoP mean velocity for MBUA and TKA during ascent and descent. Conclusions: Unconstrained squat is able to reveal differences in the functional performance among control and arthroplasty groups and between different arthroplasty designs. Considering the similarity index calculated for the variables showing statistically significance, FBUA performance appears to be closest to that of the CTR group. Level of evidence: III a. [ABSTRACT FROM AUTHOR]

The prospect and potentiality of interfacing minds with machines has long captured human imagination. Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental capabilities. Applications of brain–computer interfaces are being explored in applications as diverse as security, lie detection, alertness monitoring, gaming, education, art, and human cognition augmentation. The present tutorial aims to survey the principal features and challenges of brain–computer interfaces (such as reliable acquisition of brain signals, filtering and processing of the acquired brainwaves, ethical and legal issues related to brain–computer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications. The content of this paper is aimed at students, researchers, and practitioners to glimpse the multifaceted world of brain–computer interfacing. [ABSTRACT FROM AUTHOR]

Hemiplegia is a neurological disorder that is often detected in children with cerebral palsy. Although many studies have investigated muscular activity in hemiplegic legs, few EMG-based findings focused on unaffected limb. This study aimed to quantify the asymmetric behavior of lower-limb-muscle recruitment during walking in mild-hemiplegic children from surface-EMG and foot-floor contact features. sEMG signals from tibialis anterior (TA) and gastrocnemius lateralis and foot-floor contact data during walking were analyzed in 16 hemiplegic children classified as W1 according to Winter' scale, and in 100 control children. Statistical gait analysis, a methodology achieving a statistical characterization of gait by averaging surface-EMG-based features, was performed. Results, achieved in hundreds of strides for each child, indicated that in the hemiplegic side with respect to the non-hemiplegic side, W1 children showed a statistically significant: decreased number of strides with normal foot-floor contact; decreased stance-phase length and initial-contact sub-phase; curtailed, less frequent TA activity in terminal swing and a lack of TA activity at heel-strike. The acknowledged impairment of anti-phase eccentric control of dorsiflexors was confirmed in the hemiplegic side, but not in the contralateral side. However, a modified foot-floor contact pattern is evinced also in the contralateral side, probably to make up for balance requirements. [ABSTRACT FROM AUTHOR]

Introduction: The freezing of gait (FOG) is a common and highly distressing motor symptom in patients with Parkinson's Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment.Methods: In order to verify the acceptance of a smartphone-based architecture and its reliability at detecting FOG in real-time, we studied 20 patients suffering from PD-related FOG. They were asked to perform video-recorded Timed Up and Go (TUG) test with and without dual-tasks while wearing the smartphone. Video and accelerometer recordings were synchronized in order to assess the reliability of the FOG detection system as compared to the judgement of the clinicians assessing the videos. The architecture uses two different algorithms, one applying the Freezing and Energy Index (Moore-Bächlin Algorithm), and the other adding information about step cadence, to algorithm 1.Results: A total 98 FOG events were recognized by clinicians based on video recordings, while only 7 FOG events were missed by the application. Sensitivity and specificity were 70.1% and 84.1%, respectively, for the Moore-Bächlin Algorithm, rising to 87.57% and 94.97%, respectively, for algorithm 2 (McNemar value=28.42; p=0.0073).Conclusion: Results confirm previous data on the reliability of Moore-Bächlin Algorithm, while indicating that the evolution of this architecture can identify FOG episodes with higher sensitivity and specificity. An acceptable, reliable and easy-to-implement FOG detection system can support a better quantification of the phenomenon and hence provide data useful to ascertain the efficacy of therapeutic approaches. [ABSTRACT FROM AUTHOR]

Gait analysis is recognized as a useful assessment tool in the field of human movement research. However, doubts remain on its real effectiveness as a clinical tool, i.e. on its capability to change the diagnostic-therapeutic practice. In particular, the conditions in which evidence of a favorable cost-benefit ratio is found and the methodology for properly conducting and interpreting the exam are not identified clearly. To provide guidelines for the use of Gait Analysis in the context of rehabilitation medicine, SIAMOC (the Italian Society of Clinical Movement Analysis) promoted a National Consensus Conference which was held in Bologna on September 14th, 2013. The resulting recommendations were the result of a three-stage process entailing i) the preparation of working documents on specific open issues, ii) the holding of the consensus meeting, and iii) the drafting of consensus statements by an external Jury. The statements were formulated based on scientific evidence or experts' opinion, when the quality/quantity of the relevant literature was deemed insufficient. The aim of this work is to disseminate the consensus statements. These are divided into 13 questions grouped in three areas of interest: 1) General requirements and management, 2) Methodological and instrumental issues, and 3) Scientific evidence and clinical appropriateness. SIAMOC hopes that this document will contribute to improve clinical practice and help promoting further research in the field. [ABSTRACT FROM AUTHOR]