Evidence map›Paper›PMID 39797057›Full record

SynthesisSensors (Basel, Switzerland)2025

Movement Disorders and Smart Wrist Devices: A Comprehensive Study.

Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

Abstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Ultrasound-Informed State Estimation of Wrist Tremor Dynamics via Koopman Operator for Personalized Sensory Peripheral Nerve Stimulation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Andrea CaroppoNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0000-0003-0318-8347
Andrea ManniNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0000-0001-5716-5824
Gabriele RescioNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0000-0003-3374-2433
Anna Maria CarluccioNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0009-0009-1431-4653
Pietro Aleardo SicilianoNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0000-0002-1312-4593
Alessandro LeoneNational Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.ORCID 0000-0002-8970-3313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the medical field, there are several very different movement disorders, such as tremors, Parkinson's disease, or Huntington's disease. A wide range of motor and non-motor symptoms characterizes them. It is evident that in the modern era, the use of smart wrist devices, such as smartwatches, wristbands, and smart bracelets is spreading among all categories of people. This diffusion is justified by the limited costs, ease of use, and less invasiveness (and consequently greater acceptability) than other types of sensors used for health status monitoring. This systematic review aims to synthesize research studies using smart wrist devices for a specific class of movement disorders. Following PRISMA-S guidelines, 130 studies were selected and analyzed. For each selected study, information is provided relating to the smartwatch/wristband/bracelet model used (whether it is commercial or not), the number of end-users involved in the experimentation stage, and finally the characteristics of the benchmark dataset possibly used for testing. Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. It turned out that most of the studies have been published in the last ten years, showing a growing interest in the scientific community. The selected articles mainly investigate the relationship between smart wrist devices and Parkinson's disease. Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington's Disease, ataxia, or Tourette Syndrome. However, the results of this review highlight the difficulties still present in the use of the smartwatch/wristband/bracelet for the identified categories of movement disorders, despite the advantages these technologies could bring in the dissemination of low-cost solutions usable directly within living environments and without the need for caregivers or medical personnel.

Indexed as

Movement DisordersWearable Electronic DevicesWristAlgorithmsHumansParkinson Diseaseataxiabraceletepilepsyessential tremorgait disordersHuntington’s diseasemovement disordersParkinson’s diseasereviewseizure detectionsmartwatchTourette Syndrometremorsunilateral cerebral palsywristbandwrist-worn

Identifiers

PMID39797057
PMCPMC11723440

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.