scholarly journals A real-world study of wearable sensors in Parkinson’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jamie L. Adams ◽  
Karthik Dinesh ◽  
Christopher W. Snyder ◽  
Mulin Xiong ◽  
Christopher G. Tarolli ◽  
...  

AbstractMost wearable sensor studies in Parkinson’s disease have been conducted in the clinic and thus may not be a true representation of everyday symptoms and symptom variation. Our goal was to measure activity, gait, and tremor using wearable sensors inside and outside the clinic. In this observational study, we assessed motor features using wearable sensors developed by MC10, Inc. Participants wore five sensors, one on each limb and on the trunk, during an in-person clinic visit and for two days thereafter. Using the accelerometer data from the sensors, activity states (lying, sitting, standing, walking) were determined and steps per day were also computed by aggregating over 2 s walking intervals. For non-walking periods, tremor durations were identified that had a characteristic frequency between 3 and 10 Hz. We analyzed data from 17 individuals with Parkinson’s disease and 17 age-matched controls over an average 45.4 h of sensor wear. Individuals with Parkinson’s walked significantly less (median [inter-quartile range]: 4980 [2835–7163] steps/day) than controls (7367 [5106–8928] steps/day; P = 0.04). Tremor was present for 1.6 [0.4–5.9] hours (median [range]) per day in most-affected hands (MDS-UPDRS 3.17a or 3.17b = 1–4) of individuals with Parkinson’s, which was significantly higher than the 0.5 [0.3–2.3] hours per day in less-affected hands (MDS-UPDRS 3.17a or 3.17b = 0). These results, which require replication in larger cohorts, advance our understanding of the manifestations of Parkinson’s in real-world settings.

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Gloria Vergara-Diaz ◽  
Jean-Francois Daneault ◽  
Federico Parisi ◽  
Chen Admati ◽  
Christina Alfonso ◽  
...  

AbstractParkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks.


Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5963 ◽  
Author(s):  
Elke Warmerdam ◽  
Robbin Romijnders ◽  
Julius Welzel ◽  
Clint Hansen ◽  
Gerhard Schmidt ◽  
...  

Neurological pathologies can alter the swinging movement of the arms during walking. The quantification of arm swings has therefore a high clinical relevance. This study developed and validated a wearable sensor-based arm swing algorithm for healthy adults and patients with Parkinson’s disease (PwP). Arm swings of 15 healthy adults and 13 PwP were evaluated (i) with wearable sensors on each wrist while walking on a treadmill, and (ii) with reflective markers for optical motion capture fixed on top of the respective sensor for validation purposes. The gyroscope data from the wearable sensors were used to calculate several arm swing parameters, including amplitude and peak angular velocity. Arm swing amplitude and peak angular velocity were extracted with systematic errors ranging from 0.1 to 0.5° and from −0.3 to 0.3°/s, respectively. These extracted parameters were significantly different between healthy adults and PwP as expected based on the literature. An accurate algorithm was developed that can be used in both clinical and daily-living situations. This algorithm provides the basis for the use of wearable sensor-extracted arm swing parameters in healthy adults and patients with movement disorders such as Parkinson’s disease.


Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2631
Author(s):  
Lucy Coates ◽  
Jian Shi ◽  
Lynn Rochester ◽  
Silvia Del Din ◽  
Annette Pantall

Parkinson’s disease (PD) is a common age-related neurodegenerative disease. Gait impairment is frequent in the later stages of PD contributing to reduced mobility and quality of life. Digital biomarkers such as gait velocity and step length are predictors of motor and cognitive decline in PD. Additional gait parameters may describe different aspects of gait and motor control in PD. Sample entropy (SampEnt), a measure of signal predictability, is a nonlinear approach that quantifies regularity of a signal. This study investigated SampEnt as a potential biomarker for PD and disease duration. Real-world gait data over a seven-day period were collected using an accelerometer (Axivity AX3, York, UK) placed on the low back and gait metrics extracted. SampEnt was determined for the stride time, with vector length and threshold parameters optimized. People with PD had higher stride time SampEnt compared to older adults, indicating reduced gait regularity. The range of SampEnt increased over 36 months for the PD group, although the mean value did not change. SampEnt was associated with dopaminergic medication dose but not with clinical motor scores. In conclusion, this pilot study indicates that SampEnt from real-world data may be a useful parameter reflecting clinical status although further research is needed involving larger populations.


2019 ◽  
Vol 27 (3) ◽  
pp. S221-S222
Author(s):  
Jennifer Goldman ◽  
Susan Fox ◽  
Stuart Isaacson ◽  
Doral Fredericks ◽  
Jeffrey Trotter ◽  
...  

2018 ◽  
Vol 21 ◽  
pp. S2
Author(s):  
J Goldman ◽  
D Fredericks ◽  
J Trotter ◽  
C Heywood ◽  
A Ryan ◽  
...  

2021 ◽  
pp. 1-15
Author(s):  
Eduardo Tolosa ◽  
Georg Ebersbach ◽  
Joaquim J. Ferreira ◽  
Olivier Rascol ◽  
Angelo Antonini ◽  
...  

Background: A greater understanding of the everyday experiences of people with Parkinson’s disease (PD) and their carers may help improve clinical practice. Objective: The Parkinson’s Real-world Impact assesSMent (PRISM) study evaluated medication use, health-related quality of life (HRQoL) and the use of healthcare resources by people with PD and their carers. Methods: PRISM is an observational cross-sectional study, in which people with PD and their carers completed an online survey using structured questionnaires, including the Parkinson’s Disease Quality of Life Questionnaire (PDQ-39), Non-Motor Symptoms Questionnaire (NMSQuest) and Zarit Burden Interview (ZBI). Results: Data were collected from 861 people with PD (mean age, 65.0 years; mean disease duration, 7.7 years) and 256 carers from six European countries. People with PD reported a large number of different co-morbidities, non-motor symptoms (mean NMSQuest score, 12.8), and impaired HRQoL (median PDQ-39 summary score, 29.1). Forty-five percent of people with PD reported at least one impulse control behaviour. Treatment patterns varied considerably between different European countries. Levodopa was taken in the last 12 months by 85.9% of participants, and as monotherapy by 21.8% . Carers, who were mostly female (64.8%) and the partner/spouse of the person with PD (82.1%), reported mild to moderate burden (mean ZBI total score, 26.6). Conclusions: The PRISM study sheds light on the lives of people with PD and those who care for them, re-emphasising the many challenges they face in everyday life. The study also provides insights into the current treatment of PD in Europe.


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