Application of smart bracelet to monitor frailty‐related gait parameters of older Chinese adults: A preliminary study

Zhong, Runting; Rau, Pei‐Luen Patrick; Yan, Xinghui

doi:10.1111/ggi.13492

Cited by 31 publications

(24 citation statements)

References 31 publications

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“…In this study, we aimed to improve detection of frailty-related neuromuscular deficits based on gait performance parameters derived from unsupervised DPA. Previous studies have used trunk motion data from supervised in-lab gait tests to characterize sensorimotor gait performance among frail elders including gait variability, asymmetry, initiation, and irregularity (10,11,(13)(14)(15)(16)(17). We hypothesized that using more robust measures of unsupervised DPA gait performance (instead of number of steps) it would be possible to distinguish between non-frail and pre-frail older adults.…”

Section: Introductionmentioning

confidence: 99%

Sensor-based Characterization of Daily Walking: A New Paradigm in Frailty Assessment

Kumar

Toosizadeh

Mohler

et al. 2019

Preprint

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Background Frailty is an increasingly recognized geriatric syndrome resulting in decline in reserve across multiple physiological systems. Impaired physical function is a prime indicator of frailty.Objective The goal of this study was to develop an algorithm that discriminates between frailty groups (non-frail, pre-frail, and frail) based on gait performance parameters derived from unsupervised daily physical activity (DPA).Methods DPA was acquired for 48 hours from older adults (≥65 years) using a tri-axial accelerometer motion-sensor. Purposeful continuous bouts of walking (≥60s) without pauses were identified from acceleration data. These were then used to extract qualitative measures (gait variability, gait asymmetry, and gait irregularity) and quantitative measures (total continuous walking duration and maximum number of continuous steps) to characterize gait performance. Association between frailty and gait performance parameters was assessed using multinomial logistic models with frailty as the dependent variable, and gait performance parameters along with demographic parameters as independent variables.Results 126 older adults (44 non-frail, 60 pre-frail, and 22 frail, based on the Fried index) were recruited. Step- and stride-times, frequency domain gait variability, and purposeful walking quantitative measures were significantly different between non-frail and pre-frail as well as non-frail and frail groups ( p <0.05). Using the logistic model pre-frail/frail group (vs. non-frail) was identified with 76.8% sensitivity and 80% specificity.Discussion Everyday walking characteristics were found to be associated with frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the early stages of frailty. In-home gait assessment offers an opportunity to screen for and monitor frailty.

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Section: Introductionmentioning

confidence: 99%

Sensor-based Characterization of Daily Walking: A New Paradigm in Frailty Assessment

Kumar

Toosizadeh

Mohler

et al. 2019

Preprint

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“…Gait Irregularity: Results from supervised gait studies showed that irregularity measures can describe predictability of walking cycles, which can be influenced by both neurological and neuromuscular diseases (46)(47)(48)(49). Further, within in-lab settings, it has been demonstrated that gait irregularity can differ between non-frail and pre-frail older adults (21). We used Sample Entropy (SampEn) assessment defined as equation (2), where was defined as the number of matches in the filtered acceleration signal length (distance function smaller than tolerance ) and as the number of matches of length ( ) (50)(51)(52)(53)(54).…”

Section: Continuous Walking Boutsmentioning

confidence: 99%

“…In this study, we aimed to improve detection of frailty-related neuromuscular deficits based on gait performance parameters derived from unsupervised DPA. Previous studies have used trunk motion data from supervised in-lab gait tests to characterize sensorimotor gait performance among frail elders including gait variability, asymmetry, initiation, and irregularity (11,12,(18)(19)(20)(21)(22). We hypothesized that using more robust measures of unsupervised DPA gait performance such as gait variability, asymmetry and irregularity (instead of number of steps) it would be possible to distinguish between non-frail and pre-frail/frail older adults.…”

mentioning

confidence: 99%

Sensor-based Characterization of Daily Walking: A New Paradigm in Pre-frailty/Frailty Assessment

Kumar

Toosizadeh

Mohler

et al. 2020

Preprint

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Background: Frailty is a highly recognized geriatric syndrome resulting in decline in reserve across multiple physiological systems. Impaired physical function is one of the major indicators of frailty.Objective: The goal of this study was to evaluate an algorithm that discriminates between frailty groups (non-frail and pre-frail/frail) based on gait performance parameters derived from unsupervised daily physical activity (DPA).Methods: DPA was acquired for 48 hours from older adults (≥65 years) using a tri-axial accelerometer motion-sensor. Continuous bouts of walking for 20s, 30s, 40s, 50s and 60s without pauses were identified from acceleration data. These were then used to extract qualitative measures (gait variability, gait asymmetry, and gait irregularity) and quantitative measures (total continuous walking duration and maximum number of continuous steps) to characterize gait performance. Association between frailty and gait performance parameters was assessed using multinomial logistic models with frailty as the dependent variable, and gait performance parameters along with demographic parameters as independent variables.Results: 126 older adults (44 non-frail, 60 pre-frail, and 22 frail, based on the Fried index) were recruited.Step-and stride-times, frequency domain gait variability, and continuous walking quantitative measures were significantly different between non-frail and pre-frail/frail groups (p<0.05). Among the five different durations (20s, 30s, 40s, 50s and 60s), gait performance parameters extracted from 60s continuous walks provided the best frailty assessment results. Using the 60s gait performance parameters in the logistic model, pre-frail/frail group (vs. non-frail) was identified with 76.8% sensitivity and 80% specificity.Discussion: Everyday walking characteristics were found to be associated with frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the early stages of frailty. In-home gait assessment offers an opportunity to screen for and monitor frailty.

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“…Furthermore, when users disclose money information to human beings, they are usually seeking financial support or investment advice from others; users might not believe that IoT-CAs currently have the social capital or intelligence to provide financial support and advice. However, in terms of users' self-disclosure of body information, various IoT devices have been recently developed and applied for health care and monitoring [56,57]. Users' body information is being collected and effectively used for the detection of personal conditions and future disease prevention.…”

Section: Self-disclosure Of Information To Iot-casmentioning

confidence: 99%

Self-Disclosure to an IoT Conversational Agent: Effects of Space and User Context on Users’ Willingness to Self-Disclose Personal Information

Rau

Huang²

2019

Applied Sciences

Self Cite

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In the era of the Internet of Things (IoT), IoT conversational agents (IoT-CAs) have become the gateways for smart spaces. Users will inevitably self-disclose some types of personal information while interacting with IoT-CAs. In this study, users’ willingness to disclose different types of information to IoT-CAs in two smart spaces (living space and workspace) and two user contexts (one user or two users) was investigated. One living space and one workspace were built for users to experience interactions with IoT-CAs. Subsequently, users’ willingness to self-disclose six types of personal information was measured. Two experiments were separately conducted for a single user (N = 36) and two users (N = 48). The results indicated that users were most willing to disclose information about their tastes and interests and least willing to disclose money information. Users in the living space were willing to disclose more information than those in the workspace, which was mediated by users’ expectations for the reciprocal services of IoT-CAs rather than the awareness of other persons or external factors. Participants had a high private self-awareness in the living space and workspace; their attention was focused on themselves rather than on external factors in smart spaces.

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Application of smart bracelet to monitor frailty‐related gait parameters of older Chinese adults: A preliminary study

Abstract: The present study suggested that the decline in gait parameters as a result of frailty could be detected by the smart bracelet sensor. Geriatr Gerontol Int 2018; 18: 1366-1371.

Cited by 31 publications

References 31 publications

Sensor-based Characterization of Daily Walking: A New Paradigm in Frailty Assessment

Sensor-based Characterization of Daily Walking: A New Paradigm in Frailty Assessment

Sensor-based Characterization of Daily Walking: A New Paradigm in Pre-frailty/Frailty Assessment

Self-Disclosure to an IoT Conversational Agent: Effects of Space and User Context on Users’ Willingness to Self-Disclose Personal Information

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