Assessment of gait and posture characteristics using a smartphone wearable system for persons with osteoporosis with and without falls.

Autor: Doshi KB; Division of Endocrinology, Mayo Clinic, Scottsdale, AZ, 85259, USA., Moon SH; School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA., Whitaker MD; Division of Endocrinology, Mayo Clinic, Scottsdale, AZ, 85259, USA., Lockhart TE; School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA. Thurmon.Lockhart@asu.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Jan 11; Vol. 13 (1), pp. 538. Date of Electronic Publication: 2023 Jan 11.
DOI: 10.1038/s41598-023-27788-w
Abstrakt: We used smartphone technology to differentiate the gait characteristics of older adults with osteoporosis with falls from those without falls. We assessed gait mannerism and obtained activities of daily living (ADLs) with wearable sensor systems (smartphones and inertial measurement units [IMUs]) to identify fall-risk characteristics. We recruited 49 persons with osteoporosis: 14 who had a fall within a year before recruitment and 35 without falls. IMU sensor signals were sampled at 50 Hz using a customized smartphone app (Lockhart Monitor) attached at the pelvic region. Longitudinal data was collected using MoveMonitor+ (DynaPort) IMU over three consecutive days. Given the close association between serum calcium, albumin, PTH, Vitamin D, and musculoskeletal health, we compared these markers in individuals with history of falls as compared to nonfallers. For the biochemical parameters fall group had significantly lower calcium (P = 0.01*) and albumin (P = 0.05*) and higher parathyroid hormone levels (P = 0.002**) than nonfall group. In addition, persons with falls had higher sway area (P = 0.031*), lower dynamic stability (P < 0.001***), gait velocity (P = 0.012*), and were less able to perform ADLs (P = 0.002**). Thus, persons with osteoporosis with a history of falls can be differentiated by using dynamic real-time measurements that can be easily captured by a smartphone app, thus avoiding traditional postural sway and gait measures that require individuals to be tested in a laboratory setting.
(© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Databáze: MEDLINE
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