ReviewJournal of neural transmission (Vienna, Austria : 1996)2023
The use of wearables for the diagnosis and treatment of Parkinson's disease.
Review in Journal of neural transmission (Vienna, Austria : 1996), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Determining Falls Risk in People with Parkinson's Disease Using Wearable Sensors: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Wearable device for tremor-like motion acquisition: a low-cost device using 3D printing for research and education.HardwareX · 2026Article
- Freezing of Gait in Parkinson's Disease: A Heterogeneous Phenomenon Across Assessment Tools.The European journal of neuroscience · 2026Article
- Attentive Prototype Learning with Wearable Sensor Mutual Information for Fall Risk Stratification of Parkinson's Patients.Bioengineering (Basel, Switzerland) · 2026Article
- Weekly Variability of an Objective Bradykinesia Score in Parkinson's Disease-An Observational Longitudinal Study.Journal of clinical medicine · 2026Article
- A framework of digital biomarkers for neurodegenerative diseases.Nature reviews bioengineering · 2026Article
- Motor and non-motor fluctuations in Parkinson's disease: the knowns and unknowns of current therapeutic approaches.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Comparison of machine learning models for bradykinesia assessment using digital health technology.Frontiers in digital health · 2026Article
- Dynamic Assessment of Fine Motor Control and Vocalization in Parkinson Disease Through a Smartphone App: Cross-Sectional Study of Time-Severity Interaction Effects.JMIR mHealth and uHealth · 2025Article
- Dual stream transformer for medication state classification in Parkinson's disease patients using facial videos.NPJ digital medicine · 2025Article
- The future of Parkinson's care: a need to expand access.Frontiers in neurology · 2025Article
- Article
- [The potential of wearable technology in knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024Review
- [Commercial devices for monitoring symptoms in Parkinson's disease: benefits, limitations and trends].Revista de neurologia · 2024Review
- Patients' Expectations of Doctors' Clinical Competencies in the Digital Health Care Era: Qualitative Semistructured Interview Study Among Patients.JMIR human factors · 2024Article
- Tongue Acupuncture to Treat Dysphagia in Patients with Parkinson's Disease: A Randomized Controlled Trial.Medical acupuncture · 2024Article
- Wearable Sensors in Other Medical Domains with Application Potential for Orthopedic Trauma Surgery-A Narrative Review.Journal of clinical medicine · 2024Review
- Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics.PeerJ. Computer science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder, with increasing numbers of affected patients. Many patients lack adequate care due to insufficient specialist neurologists/geriatricians, and older patients experience difficulties traveling far distances to reach their treating physicians. A new option for these obstacles would be telemedicine and wearables. During the last decade, the development of wearable sensors has allowed for the continuous monitoring of bradykinesia and dyskinesia. Meanwhile, other systems can also detect tremors, freezing of gait, and gait problems. The most recently developed systems cover both sides of the body and include smartphone apps where the patients have to register their medication intake and well-being. In turn, the physicians receive advice on changing the patient's medication and recommendations for additional supportive therapies such as physiotherapy. The use of smartphone apps may also be adapted to detect PD symptoms such as bradykinesia, tremor, voice abnormalities, or changes in facial expression. Such tools can be used for the general population to detect PD early or for known PD patients to detect deterioration. It is noteworthy that most PD patients can use these digital tools. In modern times, wearable sensors and telemedicine open a new window of opportunity for patients with PD that are easy to use and accessible to most of the population.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.