JMIR Publications

ABSTRACT

Background:

Over the past years, a variety of technologies were developed in hospitals and treatment centers to facilitate the upper limb rehabilitation process. The requirements for the development of such devices are mainly based on functionality, usability, software, and safety. Thus, upper limb wearable devices are developed to ensure the capture of reliable data for clinical evaluations so that therapy and recovery can be understood.

Objective:

The objective of this paper is to provide 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. More specifically, this paper aims to provide a thorough review of upper limb wearable-based monitoring systems with the following objectives: To analyze the type and effectiveness of each wearable system To gauge its wearability and feasibility regarding the sensing technology To examine signal processing techniques and extracted features To classify the type and accuracy of the feedback according to the experiment results To review the findings, discuss limitations, and propose future directions

Methods:

The review was conducted based on the Bargas-Avila & Hornbæk, 2011 and Cochrane methodology 9, and it included 5 phases: Phase 1: Potentially relevant publications identified from the following electronic libraries: ACM Digital Library (ACM) IEEE Xplore (IEEE) PubMed (PM) ScienceDirect (SD) Search terms (in the publication’s title, abstract, and/or keywords): query 1: “upper limb rehabilitation” AND “wearables” query 2: (posture monitoring OR motion monitoring) AND wearables Inclusion Criteria: The papers concern motion or posture tracking of upper limbs. The studies focus on wearable devices. Feedback is given to the end-users. The system considers clinical or rehabilitation purposes. Papers were published in the last 13 years and were written in English. Exclusion Criteria: Robotic and exoskeleton systems Prosthetics and Orthosis Activity recognition systems (activity/gesture or motion capture) Reviews and books Phase 2: Publications retrieved for detailed evaluation. Phase 3: Publications to be included in the analysis Phase 4: Data Gathering Phase 5: Data Analysis

Results:

The results of this systematic review indicated that the majority of the papers were uncontrolled studies. Also, it is concluded that upper limb wearable devices provide clinical assessment by reducing the recovery time of the patients as it influences their motivation to continue their rehabilitation program. Moreover, the placement method of the devices plays a crucial role in the range of motion assessment as it impacts the interpretation of the data. Thus, the majority of the studies utilized straps as they provide more flexibility and great strength. Also, the filters utilized to capture the range of motion, posture, and the amount of use, were Butterworth, band-pass and low-pass filters. For the fusion of the data, Kalman, Madgwick, and complementary filters were significantly used. Regarding the form of the feedback, it was usually visual on a computer or a smartphone/tablet.

Conclusions:

This review aimed to provide a thorough understanding of the purpose, sensing technology, feasibility and wearability, placement of sensors, methodology, and feedback on upper-limb wearable devices. There were limitations on positioning, the number, and the possible disruptions of the sensors which are challenges that need to be overcome as they affect the limb’s computed trajectory. Thus more clinical trials need to be conducted to assess the effectiveness of the system. Future studies need to be focused on integrating the sensors and improving their usability and feasibility by providing more adaptable feedback and providing more options to the users and therapists to asses the rehabilitation.