This AI Watches You Walk to Diagnose Parkinson’s, MS

Good news! Earliest possible diagnosis is perhaps very critical for successful treatment! 

"Simply by looking at someone’s gait, clues may emerge about an underlying neurological disorder. ... Neurological disorders can often cause subtle changes in a person’s gait, even during the early-to-mid stages of disease."

From the abstract:

"This study examined the effectiveness of a vision-based framework for multiple sclerosis (MS) and Parkinson's disease (PD) gait dysfunction prediction. We collected gait video data from multi-view digital cameras during self-paced walking from MS, PD patients and age, weight, height and gender-matched healthy older adults (HOA). We then extracted characteristic 3D joint keypoints from the collected videos. In this work, we proposed a data-driven methodology to classify strides in persons with MS (PwMS), persons with PD (PwPD) and HOA that may generalize across different walking tasks and subjects. We presented a comprehensive quantitative comparison of 16 diverse traditional machine and deep learning (DL) algorithms. When generalizing from comfortable walking (W) to walking-while-talking (WT), multi-scale residual neural network achieved perfect accuracy and AUC for classifying individuals with a given gait disorder; for subject generalization in W trials, residual neural network resulted in the highest accuracy and AUC of 78.1% and 0.87 (resp.), and 1D convolutional neural network (CNN) had highest accuracy of 75% in WT trials. Finally, when generalizing over new subjects in different tasks, again 1D CNN had the top classification accuracy and AUC of 79.3% and 0.93 (resp.). This work is the first attempt to apply and demonstrate the potential of DL with a multi-view digital camera-based gait analysis framework for neurological gait dysfunction prediction. This study suggests the viability of inexpensive vision-based systems for diagnosing certain neurological disorders."

This AI Watches You Walk to Diagnose Parkinson’s, MS - IEEE Spectrum Video plus algorithms could make gait analysis cheaper

A Vision-Based Framework for Predicting Multiple Sclerosis and Parkinson's Disease Gait Dysfunctions - A Deep Learning Approach (open access)

The novel technique by Kaur and her collegues involves a side and a front camera that monitors a person’s gait, while an AI algorithm extracts features from the data that may indicate the subject has MS or Parkinson’s disease.