Linda Zhu, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, Lacie Gladding
{"title":"Reliability Check of an Assessment System for Parkinson’s Disease Tremor Monitoring With Portable Devices","authors":"Linda Zhu, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, Lacie Gladding","doi":"10.1115/imece2021-71144","DOIUrl":null,"url":null,"abstract":"\n Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor.\n A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.","PeriodicalId":314012,"journal":{"name":"Volume 5: Biomedical and Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5: Biomedical and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2021-71144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor.
A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.