Evidence map›Paper›PMID 41341986›Full record

ArticleJMIR neurotechnology2023

A Novel System to Monitor Tic Attacks for Tourette Syndrome Using Machine Learning and Wearable Technology: Preliminary Survey Study and Proposal for a New Sensing Device.

Agni Rajinikanth, Davis Kevin Clark, Marianna Evangelia Kapsetaki

Abstract read
In one paragraph

Article in JMIR neurotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
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  3. Review
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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

3 authors.

Agni Rajinikanth *Rutgers Preparatory School Somerset, NJ United States.ORCID https://orcid.org/0000-0003-3310-9689
Davis Kevin Clark *St George's School Vancouver, BC Canada.ORCID https://orcid.org/0000-0003-4264-0850
Marianna Evangelia KapsetakiFaculty of Life Sciences Division of Biosciences University College London London United Kingdom.ORCID https://orcid.org/0000-0002-0114-2276

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Tourette syndrome is a neurological disorder that is characterized by repeated unintentional physical movement and vocal sounds, better known as tics. Cases of mild Tourette can have tics numerous times throughout the day, while severe cases may have tics every 5 to 10 seconds. At certain times, typically during high levels of stress, tics become chained in an incessant, continuous fashion-this is known as a tic attack. Tic attacks incapacitate the patient, rendering it difficult for them to move, perform daily actions, and even communicate with others. Caretakers-usually guardians, family members, or nurses-can help reduce the time tic attacks last with their presence and by providing emotional support to the patient. Objective: We describe TSBand, a wearable wristband that uses machine learning algorithms and a variety of sensors to monitor for tic attacks and notify caretakers when an attack occurs. Methods: We conducted a research survey with 70 Tourette patients to determine the usability and functionality of TSBand; internal review board approval was not required. Results: This study has resulted in a smart wristband prototype that costs US $62.74; it uses movement, heart rate, sweat, and body temperature to detect tic attacks using a hybrid local outlier factoring and regression algorithm. An audio tic attack detection mechanism is also included, using recurrent neural networks, and a manually activated backup button and backup audio mechanism are fitted to alert caretakers on the personalized companion app. Conclusions: TSBand enables the caretaker to provide support faster and prevent excessive self-harm or injury during the attack. It is an affordable and effective solution, solving a problem that many Tourette patients, often children, face. This study has not had the opportunity to test TSBand with any Tourette patients, and we aim to perform rigorous testing and analysis after grant funding is secured.

Indexed as

automatic tic detectionbiosensing technologymovement disordersneurological diseasestic attacksTourette syndrometremor monitoringwearable technology

Identifiers

PMID41341986
PMCPMC12671283

What OpenQuestion holds

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Registered trials

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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.