ARMIA: A Sensorized Arm Wearable for Motor Rehabilitation

Abstract

In this paper, we present ARMIA: a sensorized arm wearable that includes a combination of inertial and sEMG sensors to interact with serious games in telerehabilitation setups. This device reduces the cost of robotic assistance technologies to be affordable for end-users at home and at rehabilitation centers. Hardware and acquisition software specifications are described together with potential applications of ARMIA in real-life rehabilitation scenarios. A detailed comparison with similar medical technologies is provided, with a specific focus on wearable devices and virtual and augmented reality approaches. The potential advantages of the proposed device are also described showing that ARMIA could provide similar, if not better, the effectivity of physical therapy as well as giving the possibility of home-based rehabilitation.

Research hotspots and trends of the tele-rehabilitation for stroke survivors based on CiteSpace: A review

“…[46,56] Finally, the practice patterns of tele-rehabilitation services after stroke are diverse. [57][58][59][60] In this case, unified guidelines or standards are needed to ensure and promote high-quality healthcare services. A scoping review found that most guidelines for tele-rehabilitation programs do not specifically address movement-related assessments and cannot effectively address the limitations of remote physical assessments, especially when patients are unable to move their bodies or have limited mobility.…”

Comparative Performance Analysis of Machine Learning Algorithms for Arm and Shoulder Exercises Using Wrist-Worn Band

“…Potential applications include enhancing training loads and exercise performance, as well as assisting with the rehabilitation of individuals with neurological diseases. Medical, sporting, and therapeutic applications of sensor-assisted arm exercises have been investigated [18]. The speed and force with which persons could bench press were tracked by accelerometers in a sensor system as shown in Figure 2.…”

Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network

“…Among these individuals, those with physical disabilities comprised the largest portion, accounting for 29.07% of the total number of people with disabilities, which amounted to 24.72 million [ 1 ]. The hand, being the most versatile limb of the human body, presents a significant challenge for individuals striving to engage in daily activities and regain functional independence in the presence of upper extremity disability [ 2 ]. The bionic robot hand is a specialized robotic system that complements or even substitutes for medical professionals in conducting patients' rehabilitation training and supporting their independent living.…”