Feasibility of a smartphone-based balance assessment system for subjects with chronic stroke

• Published in: Computer methods and programs in biomedicine Vol. 161; pp. 191 - 195
• Main Authors: Hou, You-Ruei, Chiu, Ya-Lan, Chiang, Shang-Lin, Chen, Hui-Ya, Sung, Wen-Hsu
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.07.2018
• Subjects: Acceleration; Activities of Daily Living; Adult; Aged; Assessment; Balance; Chronic Disease; Female; Healthy Volunteers; Humans; Male; Middle Aged; Monitoring, Ambulatory - methods; Paresis - diagnostic imaging; Postural Balance; Quality of Life; Research Design; Sample Size; Smartphone; Software; Stroke; Stroke - diagnostic imaging; Stroke; Smartphone; Balance; Assessment
• ISSN: 0169-2607; 1872-7565; 1872-7565
• DOI: 10.1016/j.cmpb.2018.04.027

•Smartphones have the potential to accomplish balance assessment with their built-in sensors, however, the feasibility is needed to be proved.•Smartphone-based assessment method can differentiate the balance performance of healthy adults and subjects with stroke.•Smartphones may be a convenient, easy-to-use, and valid tool for the balance assessment in subjects with chronic stroke. Stroke is a cerebral artery disease that may lead to long-term disabilities or death. Patients that survive a stroke usually suffer balance impairments, which affect their performance in activities of daily living (ADLs) and quality of life (QoL). In recent years, smartphones have become very popular and have many capabilities. Smartphone built-in sensors have shown their ability and potential in balance performance assessment. However, the feasibility of smartphones on subjects with chronic strokes remains to be proved. Therefore, the purpose of this study is to evaluate the feasibility of a smartphone-based balance assessment system for subjects with chronic stroke. Ten subjects with chronic stroke and thirteen healthy adults were recruited in the study. The smartphone HTC 10 (HTC Corporation, Taiwan) was used to perform the balance assessment, and its built-in accelerometer and gyroscope were used to record data from the subjects. Six postures were tested for thirty seconds each: shoulder-width stance (SWS) with eyes opened (E/O) and eyes closed (E/C), feet-together stance (FTS) with E/O and E/C, and semi-tandem stance (STS) with E/O and E/C. The smartphone was fixed to the back of subjects at the second sacral spine (S2) level. The changes registered in the accelerometer and gyroscope data were used to represent the balance performance, in which higher values indicate more instability. Data was analyzed using the independent t-test with the software SPSS 20, and the statistical significance level was set to α < 0.05. Significant difference in the acceleration data was found among subjects with chronic stroke and healthy adults under four assessment postures: SWS with E/C (p = 0.048), FTS with E/O (p = 0.027), FTS with E/C (p = 0.000), and STS with E/C (p = 0.048). Furthermore, according to the gyroscope data, there were significant differences in how the two groups performed the postures. The results demonstrate that a smartphone with a built-in accelerometer and gyroscope can be used to classify balance performances between healthy adults and subjects with chronic stroke. This study shows that smartphones are feasible to assess balance for subjects with chronic stroke.