Analysis of gait pattern related to high cerebral small vessel disease burden using quantitative gait data from wearable sensors

Kelin Xu, Yingzhe Wang, Yanfeng Jiang, Yawen Wang, Peixi Li, Heyang Lu, Chen Suo, Ziyu Yuan, Qi Yang, Qiang Dong, Li Jin, Mei Cui, Xingdong Chen

Abstract: Highlights•An insole-like wearable gait tracking device was used for collecting quantitative gait features.•A supervised dimension reduction method was proposed for summarizing the quantitative gait pattern associated with cerebral small vessel disease.•People with the identified gait pattern had a 25 % higher risk of a high CSVD burden.•Our model provides insights into the underlying neurobiological mechanisms and can help to identify CSVD patients in older adults.