Discrimination of Frailty Phenotype by Kinect^TM-Based Stepping Parameters.

JAR life Pub Date : 2023-12-20 eCollection Date: 2023-01-01 DOI:10.14283/jarlife.2023.17

Y Osuka, N Takeshima, N Kojima, T Kohama, E Fujita, M Kusunoki, Y Kato, W F Brechue, H Sasai

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Abstract

Background: Frailty increases the risk of falling, hospitalization, and premature death, necessitating practical early-detection tools.

Objectives: To examine the discriminative ability of Kinect^TM-based stepping parameters for identifying frailty phenotype.

Design: Population-based cross-sectional study.

Setting: Eighteen neighborhoods near Tokyo Metropolitan Institute for Geriatrics and Gerontology, Itabashi, Tokyo, Japan.

Participants: In total, 563 community-dwelling older adults aged ≥75 years without mobility limitations, neurological disease, or dementia were included.

Measurements: Step number (SN) and knee total movement distance (KMD) during a 20-s stepping test were evaluated using the Kinect^TM infrared depth sensor.

Results: The number (%) of participants with frailty were 51 (9.1). The area under the receiver operating characteristic curves (95% confidence interval) of a parameter consisting of SN and KMD for frailty was 0.72 (0.64, 0.79).

Conclusions: Stepping parameters evaluated using Kinect^TM provided acceptable ability in identifying frailty phenotype, making it a practical screening tool in primary care and home settings.

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通过基于 KinectTM 的步进参数识别虚弱表型。

背景：虚弱会增加跌倒、住院和过早死亡的风险，因此需要实用的早期检测工具：虚弱会增加跌倒、住院和过早死亡的风险，因此需要实用的早期检测工具：研究基于 KinectTM 的步态参数在识别虚弱表型方面的鉴别能力：设计：基于人群的横断面研究：地点：日本东京板桥区东京都老年医学研究所附近的 18 个社区：共纳入 563 名年龄≥75 岁、无行动不便、神经系统疾病或痴呆症的社区老年人：测量方法：使用 KinectTM 红外深度传感器评估 20 秒迈步测试中的步数（SN）和膝关节总移动距离（KMD）：结果：患有虚弱症的参与者有 51 人（9.1%）。由 SN 和 KMD 组成的衰弱参数的接收器操作特征曲线下面积（95% 置信区间）为 0.72 (0.64, 0.79)：使用 KinectTM 评估的步态参数在识别虚弱表型方面具有可接受的能力，使其成为初级保健和家庭环境中的实用筛查工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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JAR life

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