Improving research and development of wearable assistive and rehabilitation technologies: a systematic review on diversity factors.

This paper analyses diversity and intersectionality aspects in the R&D of wearable assistive and rehabilitation technologies (WEARTechs). We advocate for inclusive, innovative research that we hope will help bridge the gap between laboratories and the real world and reduce disparities in healthcare and technology development. We performed a systematic literature review of the intersections between assistive technologies and diversity and conducted a thematic analysis of the diversity factors identified in the literature.

Frequency-Domain sEMG Classification Using a Single Sensor.

Working towards the development of robust motion recognition systems for assistive technology control, the widespread approach has been to use a plethora of, often times, multi-modal sensors. In this paper, we develop single-sensor motion recognition systems. Utilising the peripheral nature of surface electromyography (sEMG) data acquisition, we optimise the information extracted from sEMG sensors.

Tactile Signatures and Hand Motion Intent Recognition for Wearable Assistive Devices.

Within the field of robotics and autonomous systems where there is a human in the loop, intent recognition plays an important role. This is especially true for wearable assistive devices used for rehabilitation, particularly post-stroke recovery. This paper reports results on the use of tactile patterns to detect weak muscle contractions in the forearm while at the same time associating these patterns with the muscle synergies during different grips.