Unknown

Dataset Information

0

Design of a Machine Learning-Assisted Wearable Accelerometer-Based Automated System for Studying the Effect of Dopaminergic Medicine on Gait Characteristics of Parkinson's Patients.


ABSTRACT: In the last few years, the importance of measuring gait characteristics has increased tenfold due to their direct relationship with various neurological diseases. As patients suffering from Parkinson's disease (PD) are more prone to a movement disorder, the quantification of gait characteristics helps in personalizing the treatment. The wearable sensors make the measurement process more convenient as well as feasible in a practical environment. However, the question remains to be answered about the validation of the wearable sensor-based measurement system in a real-world scenario. This paper proposes a study that includes an algorithmic approach based on collected data from the wearable accelerometers for the estimation of the gait characteristics and its validation using the Tinetti mobility test and 3D motion capture system. It also proposes a machine learning-based approach to classify the PD patients from the healthy older group (HOG) based on the estimated gait characteristics. The results show a good correlation between the proposed approach, the Tinetti mobility test, and the 3D motion capture system. It was found that decision tree classifiers outperformed other classifiers with a classification accuracy of 88.46%. The obtained results showed enough evidence about the proposed approach that could be suitable for assessing PD in a home-based free-living real-time environment.

SUBMITTER: Aich S 

PROVIDER: S-EPMC7049429 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

altmetric image

Publications

Design of a Machine Learning-Assisted Wearable Accelerometer-Based Automated System for Studying the Effect of Dopaminergic Medicine on Gait Characteristics of Parkinson's Patients.

Aich Satyabrata S   Pradhan Pyari Mohan PM   Chakraborty Sabyasachi S   Kim Hee-Cheol HC   Kim Hee-Tae HT   Lee Hae-Gu HG   Kim Il Hwan IH   Joo Moon-Il MI   Jong Seong Sim S   Park Jinse J  

Journal of healthcare engineering 20200218


In the last few years, the importance of measuring gait characteristics has increased tenfold due to their direct relationship with various neurological diseases. As patients suffering from Parkinson's disease (PD) are more prone to a movement disorder, the quantification of gait characteristics helps in personalizing the treatment. The wearable sensors make the measurement process more convenient as well as feasible in a practical environment. However, the question remains to be answered about  ...[more]

Similar Datasets

| S-EPMC10655429 | biostudies-literature
| S-EPMC6480623 | biostudies-literature
| S-EPMC5636070 | biostudies-literature
| S-EPMC5706419 | biostudies-literature
| S-EPMC9693970 | biostudies-literature
| S-EPMC5826846 | biostudies-literature
| S-EPMC7864964 | biostudies-literature
| S-EPMC10407620 | biostudies-literature
| S-EPMC7865022 | biostudies-literature
| S-EPMC5533840 | biostudies-other