The benefits of differentiating between the physiological and biomechanical load-response pathways in football and other (team) sports have become increasingly recognised. In contrast to physiologi...

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Measuring biomechanical loads in team sports – from lab to field

Rehabilitation is the process of treating post-stroke consequences. Impaired limbs are considered the common outcomes of stroke, which require a professional therapist to rehabilitate the impaired limbs and restore fully or partially its function. Due to the shortage in the number of therapists and other considerations, researchers have been working on developing robots that have the ability to perform the rehabilitation process. During the last two decades, different robots were invented to help in rehabilitation procedures. This paper explains the types of rehabilitation treatments and robot classifications. In addition, a few examples of well-known rehabilitation robots will be explained in terms of their efficiency and controlling mechanisms.

A Review on Upper Limb Rehabilitation Robots

Surface EMG-based gestures recognition systems are helping the disable to enjoy a better life. Academic institutes and commercial companies have been developing a lot of sEMG-based prosthesis, exoskeletons and rehabilitation systems. In this area, most studies are improving recognition accuracies by focusing on signals pre-processings, features and classifiers. But, in real-life circumstances, sEMG-based recognition performances are limited by many disturbances and variability from electrodes and subjects. In this paper, key advances of sEMG-based recognition systems are firs reviewed, then several disturbances or factors that limited sEMG-based performances and their solutions are summarized up in great detail. At last, prospections for improving sEMG-based robustness in the future are proposed.

Advances and Disturbances in sEMG-Based Intentions and Movements Recognition: A Review

Human gait is the identity of a person's style and quality of life. Reliable cognition of gait properties over time, continuous monitoring, accuracy of evaluation, and proper analysis of human gait characteristics have demonstrated their importance not only in clinical and medical studies, but also in the field of sports, rehabilitation, training, and robotics research. Focusing on walking gait, this study presents an overview on gait mechanisms, common technologies used in gait analysis, and importance of this particular field of research. Firstly, available technologies that involved in gait analysis are briefly introduced in this paper by concentrating on the usability and limitations of the systems. Secondly, key gait parameters and motion characteristics are elucidated from four angles of views; one: gait phases and gait properties; two: center of mass and center of pressure (CoM-CoP) tracking profile; three: Ground Reaction Force (GRF) and impact, and four: muscle activation. Thirdly, the study focuses on the clinical observations of gait patterns in diagnosing gait abnormalities of impaired patients. The presentation also shows the importance of gait analysis in sports to improve performance as well as to avoid risk of injuries of sports personnel. Significance of gait analysis in robotic research is also illustrated in this part where the study focuses on robot assisted systems and its possible applicability in clinical rehabilitation and sports training.

Gait analysis: systems, technologies, and importance

Crosstalk in myographic signals is a major hindrance to the understanding of local information related to individual muscle function. This review aims to analyse the problem of crosstalk in electromyography and mechanomyography. An initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals. Although correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk. The phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.

A review on crosstalk in myographic signals

A systematic review on fatigue analysis in triceps brachii using surface electromyography

Wheezes are high pitched continuous respiratory acoustic sounds which are produced as a result of airway obstruction. Computer-based analyses of wheeze signals have been extensively used for parametric analysis, spectral analysis, identification of airway obstruction, feature extraction and diseases or pathology classification. While this area is currently an active field of research, the available literature has not yet been reviewed. This systematic review identified articles describing wheeze analyses using computer-based techniques on the SCOPUS, IEEE Xplore, ACM, PubMed and Springer and Elsevier electronic databases. After a set of selection criteria was applied, 41 articles were selected for detailed analysis. The findings reveal that 1) computerized wheeze analysis can be used for the identification of disease severity level or pathology, 2) further research is required to achieve acceptable rates of identification on the degree of airway obstruction with normal breathing, 3) analysis using combinations of features and on subgroups of the respiratory cycle has provided a pathway to classify various diseases or pathology that stem from airway obstruction.

Wheeze sound analysis using computer-based techniques: a systematic review.

Hybrid markerless tracking of complex articulated motion in golf swings.

Mechanomyography based muscle movement analysis: a brief review

Wheezes are acoustic, adventitious, continues and high pitch pulmonary sounds produce due to airway obstruction, these sounds mostly exist in pneumonia and asthma patients. Artificial intelligence techniques have been extensively used for wheeze sound analysis to diagnose patient. The available literature has not yet been reviewed. In this article most recent and relevant 12 studies, from different databases related to artificial inelegance techniques for wheeze detection has been selected for detailed review. It has been noticed that now trend is going to increase in this area, for personal assistance and continues monitoring of patient health. The literature reveals that 1) wheezes signals have enough information for the classification of patients according to disease severity level and type of disease, 2) significant work is required for identification of severity level of airway obstruction and pathology differentiation.

Lam Chee Kiang

Papers

A systematic review on fatigue analysis in triceps brachii using surface electromyography

Wheeze sound analysis using computer-based techniques: a systematic review.

Hybrid markerless tracking of complex articulated motion in golf swings.

Mechanomyography based muscle movement analysis: a brief review

Artificial Intelligence Techniques Used for Wheeze Sounds Analysis: Review