比较专业和日常可穿戴技术在不同身体位置记录步态扰动的效果。

PLOS digital health Pub Date : 2024-08-30 eCollection Date: 2024-08-01 DOI:10.1371/journal.pdig.0000553
Lea Feld, Lena Schell-Majoor, Sandra Hellmers, Jessica Koschate, Andreas Hein, Tania Zieschang, Birger Kollmeier
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引用次数: 0

摘要

跌倒是老年人的一个重要健康问题,因此预防跌倒至关重要。由于跌倒通常是对滑倒和绊倒等步态干扰做出不当反应的结果,因此步态干扰检测越来越受到研究的关注。然而,迄今为止还没有研究利用助听器或智能手机等日常可穿戴设备在不同身体位置进行扰动检测。研究人员在分带跑步机上对 66 名参与者进行了扰动检测,同时使用助听器、智能手机和专业惯性测量单元(IMU)在不同位置(左/右耳、上衣口袋、双肩包、裤子口袋、左/右脚、左/右手腕、腰部、胸骨)记录数据。对数据进行了目测,并计算了整个试验和不同扰动条件下的最大交叉相关中值。结果显示,助听器和 IMU 在测量加速度数据方面表现相当(左助听器的相关系数为 0.93,右助听器的相关系数为 0.99),这强调了利用助听器中的传感器测量头部加速度的潜力。此外,数据还表明,使用单个助听器进行测量就足够了,第二个助听器不会带来额外的价值。此外,耳部位置、上衣口袋位置、腰部位置(相关系数约为 0.8)或胸骨位置(相关系数约为 0.9)的加速度模式相似。这些相关性或多或少与扰动类型无关。从日常可穿戴设备获得的数据似乎代表了人体在扰动过程中的运动,与专业设备的数据相似。结果表明,放置在躯干上的助听器和智能手机中的 IMU 非常适合用于步态扰动的自动检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of professional and everyday wearable technology at different body positions in terms of recording gait perturbations.

Falls are a significant health problem in older people, so preventing them is essential. Since falls are often a consequence of improper reaction to gait disturbances, such as slips and trips, their detection is gaining attention in research. However there are no studies to date that investigated perturbation detection, using everyday wearable devices like hearing aids or smartphones at different body positions. Sixty-six study participants were perturbed on a split-belt treadmill while recording data with hearing aids, smartphones, and professional inertial measurement units (IMUs) at various positions (left/right ear, jacket pocket, shoulder bag, pants pocket, left/right foot, left/right wrist, lumbar, sternum). The data were visually inspected and median maximum cross-correlations were calculated for whole trials and different perturbation conditions. The results show that the hearing aids and IMUs perform equally in measuring acceleration data (correlation coefficient of 0.93 for the left hearing aid and 0.99 for the right hearing aid), which emphasizes the potential of utilizing sensors in hearing aids for head acceleration measurements. Additionally, the data implicate that measurement with a single hearing aid is sufficient and a second hearing aid provides no added value. Furthermore, the acceleration patterns were similar for the ear position, the jacket pocket position, and the lumbar (correlation coefficient of about 0.8) or sternal position (correlation coefficient of about 0.9). The correlations were found to be more or less independent of the type of perturbation. Data obtained from everyday wearable devices appears to represent the movements of the human body during perturbations similar to that of professional devices. The results suggest that IMUs in hearing aids and smartphones, placed at the trunk, could be well suited for an automatic detection of gait perturbations.

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