Smartphones for Remote Symptom Monitoring of Parkinson’s Disease

Journal of Parkinson s Disease ◽

10.3233/jpd-202453 ◽

2021 ◽

pp. 1-5

Author(s):

Max A. Little

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Symptom Severity ◽

Computational Analysis ◽

Computational Algorithms ◽

Objective Data ◽

Future Prospects ◽

Symptom Monitoring ◽

Sensor Devices ◽

Symptoms And Signs

Parkinson’s disease is a complex and heterogeneous condition, and there are many gaps in the medical community’s scientific and practical understanding of the disease. Closing these gaps relies on objective data about symptoms and signs, collected over long durations. Smartphones contain sensor devices which can be used to remotely capture behavioral signals. From these signals, computational algorithms can distill metrics of symptom severity and progression. This brief review introduces the main concepts of the discipline, addressing the experimental, hardware and software logistics, and computational analysis. The article finishes with an exploration of future prospects for the technology.

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Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease

Scientific Data ◽

10.1038/s41597-021-00831-z ◽

2021 ◽

Vol 8 (1) ◽

Cited By ~ 1

Author(s):

Gloria Vergara-Diaz ◽

Jean-Francois Daneault ◽

Federico Parisi ◽

Chen Admati ◽

Christina Alfonso ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Symptom Severity ◽

Wearable Sensors ◽

Motor Fluctuations ◽

Sensor Data ◽

Accelerometer Data ◽

Motor Tasks ◽

Specific Symptom ◽

At Home

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.

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Synergy of pandemics-social isolation is associated with worsened Parkinson severity and quality of life

npj Parkinson s Disease ◽

10.1038/s41531-020-00128-9 ◽

2020 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Indu Subramanian ◽

Joshua Farahnik ◽

Laurie K. Mischley

Keyword(s):

Quality Of Life ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Social Isolation ◽

Support Groups ◽

Symptom Severity ◽

Social Performance ◽

Social Distancing ◽

Patient Reported

Abstract Social isolation and its deleterious effects on health increases with age in the general population. People with Parkinson’s Disease (PWP) are no exception. Social isolation is a risk factor for worsened health outcomes and increased mortality. Symptoms such as depression and sleep dysfunction are adversely affected by loneliness. There is a paucity of research on social isolation in Parkinson’s disease (PD), which is all the more critical now in the setting of social distancing due to COVID-19. The goal of this study was to survey individuals with PD to evaluate whether social isolation is associated with PD symptom severity and quality of life. Only individuals reporting a diagnosis of idiopathic PD were included in this analysis. The primary outcome measures were the Patient-Reported Outcomes in PD (PRO-PD) and questions from PROMIS Global related to social health. PRO-PD scores increased as social performance and social satisfaction scores diminished. Individuals who reported being lonely experienced a 55% greater symptom severity than those who were not lonely (P < 0.01). Individuals who documented having a lot of friends had 21% fewer symptoms than those with few or no friends (P < 0.01). Social isolation was associated with greater patient-reported PD severity and lower quality of life, although it is unclear whether this is the cause and/or a consequence of the disease. In essence, the Parkinson pandemic and the pandemic of social isolation have been further compounded by the recent COVID-19 pandemic. The results emphasize the need to keep PWP socially connected and prevent loneliness in this time of social distancing. Proactive use of virtual modalities for support groups and social prescribing should be explored.

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The Impact of the COVID-19 Pandemic on Psychological Distress, Physical Activity, and Symptom Severity in Parkinson’s Disease

Journal of Parkinson s Disease ◽

10.3233/jpd-202251 ◽

2020 ◽

Vol 10 (4) ◽

pp. 1355-1364 ◽

Cited By ~ 1

Author(s):

Anouk van der Heide ◽

Marjan J. Meinders ◽

Bastiaan R. Bloem ◽

Rick C. Helmich

Keyword(s):

Physical Activity ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Psychological Distress ◽

Symptom Severity ◽

Neuropsychiatric Symptoms ◽

Lifestyle Changes ◽

Personality Factors ◽

Reduced Physical Activity ◽

The Impact

Background: The ongoing COVID-19 pandemic has many consequences for people with Parkinson’s disease (PD). Social distancing measures complicate regular care and result in lifestyle changes, which may indirectly cause psychological stress and worsening of PD symptoms. Objective: To assess whether the COVID-19 pandemic was associated with increased psychological distress and decreased physical activity in PD, how these changes related to PD motor and non-motor symptom severity, and what frequency and burden of COVID-related stressors were. Methods: We sent an online survey to the Personalized Parkinson Project (PPP) cohort (n = 498 PD patients) in the Netherlands. In the survey, we distinguished between COVID-related stressor load, psychological distress, PD symptom severity, and physical activity. We related inter-individual differences to personality factors and clinical factors collected before the pandemic occurred. Results: 358 PD patients completed the survey between April 21 and May 25, 2020 (response rate 71.9%). Patients with higher COVID-related stressor load experienced more PD symptoms, and this effect was mediated by the degree of psychological distress. 46.6% of PD patients were less physically active since the COVID-19 pandemic, and reduced physical activity correlated with worse PD symptoms. Symptoms that worsened most were rigidity, fatigue, tremor, pain and concentration. Presence of neuropsychiatric symptoms (anxiety, depression) before the pandemic, as well as cognitive dysfunction and several personality traits predicted increased psychological distress during the COVID-19 pandemic. Conclusion: Our findings show how an external stressor (the COVID-19 pandemic) leads to a worsening of PD symptoms by evoking psychological distress as well as lifestyle changes (reduced physical activity).

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The unresolved role of mitochondrial DNA in Parkinson's disease: An overview of published studies, their limitations, and future prospects

Neurochemistry International ◽

10.1016/j.neuint.2019.104495 ◽

2019 ◽

Vol 129 ◽

pp. 104495 ◽

Cited By ~ 5

Author(s):

Amica C. Müller-Nedebock ◽

Rebecca R. Brennan ◽

Marianne Venter ◽

Ilse S. Pienaar ◽

Francois H. van der Westhuizen ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Mitochondrial Dna ◽

Future Prospects

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Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

Journal of The Royal Society Interface ◽

10.1098/rsif.2010.0456 ◽

2010 ◽

Vol 8 (59) ◽

pp. 842-855 ◽

Cited By ~ 128

Author(s):

Athanasios Tsanas ◽

Max A. Little ◽

Patrick E. McSharry ◽

Lorraine O. Ramig

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Signal Processing ◽

Symptom Severity ◽

Large Scale ◽

Rating Scale ◽

Signal Processing Algorithm ◽

Wide Range ◽

Signal Processing Algorithms ◽

Processing Algorithms

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

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