Wireless accelerometer configuration for monitoring Parkinson’s disease hand tremor

2013 ◽  
Vol 02 (02) ◽  
pp. 62-67 ◽  
Author(s):  
Robert LeMoyne ◽  
Timothy Mastroianni ◽  
Warren Grundfest
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Hand Tremor ◽  
Wireless Accelerometer

scholarly journals A mobile app for tracking non-motor symptoms of people with Parkinson’s disease: A usability study

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 890-890
Author(s):  
JuHee Lee ◽  
Yujin Suh ◽  
Yielin Kim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Tracking System ◽  
Smart Phone ◽  
Telephone Counseling ◽  
Mobile App ◽  
Motor Symptoms ◽  
Hand Tremor ◽  
Non Motor Symptoms

Abstract Smart phone-based technology for people with Parkinson’s disease has been developed worldwide. Unmonitored non-motor symptoms decrease quality of life of people with Parkinson’s disease, so the needs for technology to manage non-motor symptoms are increasing. The technology is needed to detect subtle changes in non-motor symptoms by healthcare professional. There is no mobile app which manage comprehensive symptoms of Parkinson’s disease including non-motor symptoms. It is necessary to develop a new tracking system that can effectively manage non-motor symptoms as well as motor symptoms of Parkinson’s disease. We developed a prototype of mobile app for Android smartphones, with cooperation with Mazelone company. we also have shaped functions for monitoring of motor symptoms and medication adherence. It also provided a section for caregivers to use on behalf of people with Parkinson’s disease who have difficulty to use app due to hand tremor. Through Delphi technique, we obtained content validity from eight medical and nursing experts on the contents of the application. We provided regular telephone counseling to improve and encourage their app usage. Fifteen participants used the app for 6 weeks. To evaluate usability of mobile app, we provided constructed questionnaire and conducted individual telephone interview. A mobile app for tracking non-motor symptoms demonstrated high usability and satisfaction. We learned lessons about facilitators and barriers when implementing an app such as perception and acceptance of mobile technology. The mobile app will improve continuum of care. Future studies need to improve the contents and refine technical approach for people with Parkinson’s disease.

Family history of hand tremor in patients with early Parkinson’s disease

2021 ◽  
Vol 90 ◽  
pp. 161-164
Author(s):  
Seong-Min Choi ◽  
Soo Hyun Cho ◽  
Kyung Wook Kang ◽  
Jae-Myung Kim ◽  
Byeong C. Kim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Family History ◽  
Hand Tremor ◽  
History Of ◽  
Early Parkinson’S Disease

scholarly journals A Mobile Application for Smart Computer-Aided Self-Administered Testing of Cognition, Speech, and Motor Impairment

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3236 ◽  
Author(s):  
Andrius Lauraitis ◽  
Rytis Maskeliūnas ◽  
Robertas Damaševičius ◽  
Tomas Krilavičius
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Energy Expenditure ◽  
Huntington's Disease ◽  
Huntington’S Disease ◽  
Mobile Application ◽  
Speech Analysis ◽  
Finger Tapping ◽  
Hand Tremor ◽  
Neural Impairment

We present a model for digital neural impairment screening and self-assessment, which can evaluate cognitive and motor deficits for patients with symptoms of central nervous system (CNS) disorders, such as mild cognitive impairment (MCI), Parkinson’s disease (PD), Huntington’s disease (HD), or dementia. The data was collected with an Android mobile application that can track cognitive, hand tremor, energy expenditure, and speech features of subjects. We extracted 238 features as the model inputs using 16 tasks, 12 of them were based on a self-administered cognitive testing (SAGE) methodology and others used finger tapping and voice features acquired from the sensors of a smart mobile device (smartphone or tablet). Fifteen subjects were involved in the investigation: 7 patients with neurological disorders (1 with Parkinson’s disease, 3 with Huntington’s disease, 1 with early dementia, 1 with cerebral palsy, 1 post-stroke) and 8 healthy subjects. The finger tapping, SAGE, energy expenditure, and speech analysis features were used for neural impairment evaluations. The best results were achieved using a fusion of 13 classifiers for combined finger tapping and SAGE features (96.12% accuracy), and using bidirectional long short-term memory (BiLSTM) (94.29% accuracy) for speech analysis features.

24-h Assessment of Tremor Activity and Posture in Parkinson's Disease by Multi-Channel Accelerometry

1999 ◽  
Vol 13 (4) ◽  
pp. 245-256 ◽  
Author(s):  
M. Smeja ◽  
F. Foerster ◽  
G. Fuchs ◽  
D. Emmans ◽  
A. Hornig ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Ambulatory Monitoring ◽  
Emotional Reactions ◽  
Task Demands ◽  
Diurnal Changes ◽  
Postural Tremor ◽  
Hand Tremor ◽  
Left Hand ◽  
Psychophysiological Investigation

Abstract This study describes a new method, based on accelerometry, which quantifies tremor activity and posture continuously. A total of 25 right-handed patients with Parkinson's disease were recorded in a rest condition and in a postural tremor test, and during 24-h ambulatory monitoring. The tremor parameters, such as amplitude, frequency, and occurrence (percent of time), were derived by joint amplitude-frequency analysis. The DC components of multi-channel accelerometry allowed the detection of posture. A repeated measurement MANOVA was used to test the effects of posture and night-day differences in tremor activity. Further issues included consistencies of amplitude measurements across hands, between tasks, and between segments of recordings. Findings indicated an increase between resting tremor and postural tremor in the three tremor parameters, an increase under distraction, and enhanced activity in sitting compared to standing/walking. The best predictions of daytime monitoring measures, based on resting measures, were made for left hand tremor. This methodology is suitable for the detection of diurnal changes in tremor activity, especially amplitude changes, and for the psychophysiological investigation of enhanced tremor caused by task demands and emotional reactions.

scholarly journals Unilateral loss of the swallow tail sign in a patient with idiopathic Parkinson’s disease

2021 ◽  
Vol 3 (3) ◽  
pp. 59-62
Author(s):  
Anna Misyail Abd Rashid ◽  
Mohamad Syafeeq Faeez Md Noh ◽  
Abdul Hanif Khan Yusof Khan ◽  
Mohd Naim Mohd Yaakob ◽  
Norafida Bahari ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Predictive Value ◽  
Early Stage ◽  
Imaging Biomarker ◽  
Idiopathic Parkinson’S Disease ◽  
Yahr Stage ◽  
Hand Tremor ◽  
Idiopathic Parkinson's Disease

A 66-year-old man with underlying hypertension and dyslipidemia presented with left hand tremor for one year. He also noticed difficulty in initiating movement and slowness in activities of daily living. On examination, he was noted to have mask-like facies with reduced blinking and monotonous speech. There was presence of resting pill-rolling tremor, bradykinesia, and cogwheel rigidity which was worst on the left upper limb. Gait assessment revealed difficulty in standing up, shuffling gait with reduced arm swing which was more prominent on the left side, and turning in numbers. No cerebellar signs and supranuclear palsy were present to suggest Parkinson-plus syndrome. Susceptibility weighted imaging (SWI) showed loss of the swallow tail sign on the right side [Figure 1]. The clinical presentation, supplemented by the imaging findings were concluded to be pathognomonic of idiopathic Parkinson’s disease (IPD), Hoehn & Yahr stage 1. He was started on levodopa and benserazide twice daily with improvement of symptoms.The nigrosomes are primary subregions of the substantia nigra where dopaminergic cells are lost in IPD. Within these nigrosomes, maximal cell loss occurs in nigrosome-1; the largest subgroup of nigrosomes. Normally, they appear as a SWI-hyperintense area surrounded by hypointensity within the dorsolateral substantia nigra, akin to a swallow’s tail. In one study, poor visualization of nigrosome-1 was significantly associated with higher motor asymmetry in the contralateral side (sensitivity 98.5%, specificity 93.6%, positive-predictive value 98.3%, negative-predictive value 98.3% and an accuracy of 96%) [1]. Noh et al [2] showed that abnormality involving nigrosome-1 can be detected at 3T MR imaging with an accuracy of 94.6%. Due to the difficulty in diagnosis of early stage IPD, a loss of the swallow tail sign serves as a useful imaging biomarker to supplement the clinical diagnosis, as seen in our patient.

Quantitative Motor Assessment, Detection, and Suppression of Parkinson’s Disease Hand Tremor: A Literature Review

2016 ◽  
Author(s):  
Khoi Ly ◽  
Aimee Cloutier ◽  
James Yang
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scales ◽  
Rating Scale ◽  
Research Area ◽  
Hand Tremor ◽  
Active Research ◽  
State Of Research ◽  
Future Direction ◽  
Cognitive Problems

Parkinson’s disease (PD) is difficult to detect before the onset of symptoms; further, PD symptoms share characteristics with symptoms of other diseases, making diagnosis of PD a challenging task. Without proper diagnosis and treatment, PD symptoms including tremor, bradykinesia, and cognitive problems deteriorate quickly into patients’ late life. Among them, the most distinguishable manifestations of PD are rest and postural tremor. Tremor is defined as an involuntary shaking or quivering movement of the hands or feet. Unified Parkinson’s Disease Rating Scale (UPDRS), Hoehn and Yahr (H&Y) scales are the most common rating scales that quantify the severity of PD. Due to the lack of consistency in these diagnostic tests, researchers are looking for devices for quantification and detection that can provide more objective PD motor assessments. Additionally, since there is currently no cure for PD, temporary PD symptom suppression is an active research area for improving patients’ quality of life. In this survey, the current state of research on Parkinson’s disease hand tremor quantification, detection, and suppression is discussed, especially focusing on electromechanical devices. The future direction of research on these devices is also considered.

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