HIGHLIGHTS
SUMMARY
Recent advances in data_analysis and wearable sensors for human movement moni‐ toring can promote objective and accurate clinical evaluation of neurological symptoms and improve outcome measures in clinical trials. The authors evaluated the applicability of supervised ML algorithms for classi‐ fying gait abnormalities in people with Parkinson`s disease (pwPD) based on IMU‐ derived gait parameters. pwPD suffer from gait abnormalities that closely correlate with disease progression and falls risk and affect their quality of life. Alt‐ hough machine_learning algorithms are increasingly being used for gait analysis, few studies have applied ML‐based classification . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.