Evidence map›Paper›PMID 40363202›Full record

ArticleSensors (Basel, Switzerland)2025

A Wearable Internet of Things-Based Device for the Quantitative Assessment of Hand Tremors in Parkinson's Disease: The ELENA Project.

Yessica Saez, Cristian Ureña, Julia Valenzuela, Antony García, Edwin Collado

Abstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Yessica SaezUniversidad Tecnológica de Panamá, Panama City 0819-07289, Panama.ORCID 0000-0003-0823-2490
Cristian UreñaUniversidad Tecnológica de Panamá, Panama City 0819-07289, Panama.
Julia ValenzuelaMinisterio de Salud, Hospital Regional Anita Moreno, La Villa de Los Santos 0819-11380, Panama.
Antony GarcíaUniversidad Tecnológica de Panamá, Panama City 0819-07289, Panama.ORCID 0000-0002-5795-2104
Edwin ColladoUniversidad Tecnológica de Panamá, Panama City 0819-07289, Panama.ORCID 0000-0002-0614-6428

Funding

Secretaría Nacional de Ciencia, Tecnología e Innovación 200-2022
6 · The paper itself

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms, with tremors being one of the most prominent. Traditional assessment methods, such as the Unified Parkinson's Disease Rating Scale (UPDRS), rely on subjective, intermittent evaluations, which can miss symptom fluctuations. This study presents the development and validation of the ELENA system, an IoT-based wearable device designed for the continuous monitoring of tremors in PD patients and medication tracking in PD patients. Named in honor of a 67-year-old woman who has lived with Parkinson's since 2011 and inspired the project, the ELENA system integrates an MPU6050 accelerometer, an ESP32 microcontroller, and cloud-based data analysis and MATLAB. The ELENA system was calibrated and validated against an Apple Watch, demonstrating high accuracy with frequency deviations under 0.5% and an average percentage error of -0.37%. Unlike commercial devices, ELENA offers a clinical-grade solution with customizable data access and visualization tailored for healthcare providers. Participants, including PD patients and a non-PD control group, completed a series of clinical tasks to evaluate tremor monitoring capabilities. The results showed that the system effectively captured tremor frequency and amplitude, enabling the analysis of resting, action, and postural tremors. This study highlights the ELENA system's potential to enhance PD management by providing real-time, remote monitoring of tremors. The scalable, cost-effective solution supports healthcare professionals in tracking disease progression and optimizing treatment plans, paving the way for improved patient outcomes.

Indexed as

HandInternet of ThingsParkinson DiseaseTremorWearable Electronic DevicesAccelerometryAgedFemaleHumansMaleinertial sensinginternet of thingsParkinson’s diseasetremor analysistremor monitoring

Identifiers

PMID40363202
PMCPMC12074293

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.