JMIR Publications

ABSTRACT

Background:

The development of wearable solutions for tracking upper limb motion has gained research interest over the past decade. This paper provides a systematic review of related research work on the type, feasibility, signal processing techniques, and feedback of wearable systems for tracking upper limb motion, mostly in rehabilitation applications, to understand and monitor human movement.

Objective:

The aim of this article is to investigate how wearables are used to capture upper limb functions, especially as related to clinical and rehabilitation applications.

Methods:

A systematic literature search identified twenty-seven relevant studies, published in English from 2011 to 2023, across four databases; ACM Digital Library (ACM), IEEE Xplore (IEEE), PubMed (PM), and ScienceDirect (SD). The inclusion criteria required papers focusing on motion or posture tracking for upper limbs, wearable devices, feedback given to the end-users, and the system considering clinical or rehabilitation purposes. Excluded were papers focusing on exoskeletons, robotics, prosthetics, orthosis, activity recognition systems, reviews, and books.

Results:

The results from this research focus on wearable devices that are designed to monitor upper limb movement. More specifically, the studies were divided into two distinct categories; clinical motion tracking (56%) and rehabilitation (44%), involving healthy individuals and patients, in a total of 439 participants. Of the twenty-seven studies, the majority of them (19/27) used inertial measurement units to track upper-limb movement or smart textiles embedded with sensors. These devices were attached to the body with straps (mostly Velcro), providing flexibility and stability. The developed wearable devices positively affect users' motivation, through the provided feedback – visual feedback being the most common, due to the high level of independence they provide. Moreover, a variety of signal processing techniques, such as Kalman and Butterworth filters, were applied to ensure data accuracy. However, limitations persist and include the sensor’s positioning, calibration, battery life, and the lack of clinical data on the effectiveness of the systems. The sampling rates of the data collection ranged significantly, from 50 Hz to 2000 Hz, which notably affected data quality and battery life. In addition, several findings were inconclusive, yielding further future research to understand and improve the upper limb posture to develop progressive wearable systems.

Conclusions:

This paper offers a comprehensive overview of wearable-based monitoring systems, specifically focusing on upper-limb motion tracking and rehabilitation. It emphasizes the various types of available solutions, their efficacy, wearability, feasibility, and proposed processing techniques. Finally, it presents robust findings regarding feedback accuracy derived from experiments and outlines potential future research directions.