MYO Armband for physiotherapy healthcare: A case study using gesture recognition application

Abstract

As there is a need for innovative and new medical technologies in the healthcare, we identified Thalmic's “MYO Armband”, which is used for gaming systems and controlling applications in mobiles and computers. We can exploit this development in the field of medicine and healthcare to improve public health care system. So, we spotted “MYO diagnostics”, a computer-based application developed by Thalmic labs to understand Electromyography (EMG) lines (graphs), bits of vector data, and electrical signals of our complicated biology inside our arm. The human gestures will allow to gather huge amount of data and series of EMG lines which can be analysed to detect medical abnormalities and hand movements. This application has powerful algorithms which are translated into commands to recognise human hand gestures. The effect of doctors experience on user satisfaction metrics in using MYO armband can be measured in terms of effectiveness, efficiency and satisfaction which are based on the metrics-task completion, error counts, task times and satisfaction scores. In this paper, we considered only satisfaction metrics using a widely used System Usability Scale (SUS) questionnaire model to study the usability on the twenty-four medical students of the Brighton and Sussex Medical School. This helps in providing guidelines about the use of MYO armband for physiotherapy analysis by the doctors and patients. Another questionnaire with a focus on ergonomic (human factors) issues related to the use of the device such as social acceptability, ease of use and ease of learning, comfort and stress, attempted to discover characteristics of hand gestures using MYO. The results of this study can be used in a way to support the development of interactive physiotherapy analysis by individuals using MYO and hand gesture applications at their home for self-examination. Also, the relationship and correlation between the signals received will lead to a better understanding of the whole myocardium system and assist doctors in early diagnosis.