Journal
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
Volume 18, Issue 6, Pages 1839-1847Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JBHI.2014.2301449
Keywords
Body sensor networks; mobile nodes; patient rehabilitation; wearable sensors
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Funding
- Singapore Millennium Foundation
- NUS MOE Tier 1 Grant [R263-000-A42-112]
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The range of motion (ROM) in stroke patients is often severely affected. Poststroke rehabilitation is guided through the use of clinical assessment scales for the rROM. Unfortunately, these scales are not widely utilized in clinical practice as they are excessively time-consuming. Although commercial motion-capture systems are capable of providing the information required for the assessments, most systems are either too costly or lack the convenience required for assessments to be conducted on a daily basis. This paper presents the design and implementation of a smartphone-based system for automated motor assessment using low-cost off-the-shelf inertial sensors. The system was used to automate a portion of the upper-extremity Fugl-Meyer assessment (FMA), which is widely used to quantify motor deficits in stroke survivors. Twelve out of 33 items were selected, focusing mainly on joint angle measurements of the upper body. The system has the ability to automatically identify the assessment item being conducted, and calculate the maximum respective joint angle achieved. Preliminary results show the ability of this system to achieve comparable results to goniometer measurements, while significantly reducing the time required to conduct the assessments. The portability and ease-of-use of the system would simplify the task of conducting range-of-motion assessments.
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