Simple smartphone-based assessment of gait characteristics in Parkinson disease: Validation study

Su，Dongning1; Liu，Zhu1; Jiang，Xin2,3,4; Zhang，Fangzhao5; Yu，Wanting6; Ma，Huizi1; Wang，Chunxue1; Wang，Zhan1; Wang，Xuemei1; Hu，Wanli7; Manor，Brad6,8; Feng，Tao1; Zhou，Junhong6,8,9

2021-02-01

10.2196/25451

JMIR mHealth and uHealth   影响因子和分区

2291-5222

Background: Parkinson disease (PD) is a common movement disorder. Patients with PD have multiple gait impairments that result in an increased risk of falls and diminished quality of life. Therefore, gait measurement is important for the management of PD. Objective: We previously developed a smartphone-based dual-task gait assessment that was validated in healthy adults. The aim of this study was to test the validity of this gait assessment in people with PD, and to examine the association between app-derived gait metrics and the clinical and functional characteristics of PD. Methods: Fifty-two participants with clinically diagnosed PD completed assessments of walking, Movement Disorder Society Unified Parkinson Disease Rating Scale III (UPDRS III), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety (HAM-A), and Hamilton Depression (HAM-D) rating scale tests. Participants followed multimedia instructions provided by the app to complete two 20-meter trials each of walking normally (single task) and walking while performing a serial subtraction dual task (dual task). Gait data were simultaneously collected with the app and gold-standard wearable motion sensors. Stride times and stride time variability were derived from the acceleration and angular velocity signal acquired from the internal motion sensor of the phone and from the wearable sensor system. Results: High correlations were observed between the stride time and stride time variability derived from the app and from the gold-standard system (r=0.98-0.99, P<.001), revealing excellent validity of the app-based gait assessment in PD. Compared with those from the single-task condition, the stride time (F=14.1, P<.001) and stride time variability (F=6.8, P=.008) in the dual-task condition were significantly greater. Participants who walked with greater stride time variability exhibited a greater UPDRS III total score (single task: β=.39, P<.001; dual task: β=.37, P=.01), HAM-A (single-task: β=.49, P=.007; dual-task: β=.48, P=.009), and HAM-D (single task: β=.44, P=.01; dual task: β=.49, P=.009). Moreover, those with greater dual-task stride time variability (β=.48, P=.001) or dual-task cost of stride time variability (β=.44, P=.004) exhibited lower MoCA scores. Conclusions: A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.

Gait Parkinson disease Smartphone Stride time (variability) Validity

SCI

英语

其他

WOS:000668817100016

2-s2.0-85101869222

Scopus

1.Department of Neurology,Beijing Tiantan Hospital,Beijing,China
2.The Second Clinical Medical College,Jinan University,Guangzhou,China
3.Department of Geriatrics,Shenzhen People’s Hospital,Shenzhen, Guangdong,China
4.The First Affiliated Hospital,Southern University of Science and Technology,Shenzhen, Guangdong,China
5.Department of Computer Science,The University of British Columbia,Vancouver,Canada
6.Hinda and Arthur Marcus Institute for Aging Research,Hebrew SeniorLife,Roslindale,United States
7.Department of Hematology and Oncology,Jingxi Campus,Capital Medical University,Beijing ChaoYang Hospital,Beijing,China
8.Beth Israel Deaconess Medical Center,Boston,United States
9.Harvard Medical School,Boston,United States

Su，Dongning,Liu，Zhu,Jiang，Xin,et al. Simple smartphone-based assessment of gait characteristics in Parkinson disease: Validation study[J]. JMIR mHealth and uHealth,2021,9(2).

Su，Dongning.,Liu，Zhu.,Jiang，Xin.,Zhang，Fangzhao.,Yu，Wanting.,...&Zhou，Junhong.(2021).Simple smartphone-based assessment of gait characteristics in Parkinson disease: Validation study.JMIR mHealth and uHealth,9(2).

Su，Dongning,et al."Simple smartphone-based assessment of gait characteristics in Parkinson disease: Validation study".JMIR mHealth and uHealth 9.2(2021).