NCT07066462

Brief Summary

The goal of this research study is to develop an AI-based model to detect physical fatigue in healthy young adults. The main questions it aims to answer are:

  • Perform moderate to high intensity physical exercises, including static bicycling and dumbbell squats, while wearing non-invasive sensors that measure muscle activity (sEMG), heart rate (HR), and brain activity (EEG).
  • Before starting the exercises, participants will complete a brief warm-up session that includes stretching and mobility movements.
  • Each participant undergoes two training sessions, with pre- and post-evaluations of their physical fitness status and static muscle strength.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
17

participants targeted

Target at below P25 for not_applicable

Timeline
Completed

Started Mar 2025

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

March 1, 2025

Completed
4 months until next milestone

First Submitted

Initial submission to the registry

June 17, 2025

Completed
28 days until next milestone

First Posted

Study publicly available on registry

July 15, 2025

Completed
2 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

August 31, 2025

Completed
3 months until next milestone

Study Completion

Last participant's last visit for all outcomes

November 30, 2025

Completed
Last Updated

April 13, 2026

Status Verified

April 1, 2026

Enrollment Period

6 months

First QC Date

June 17, 2025

Last Update Submit

April 7, 2026

Conditions

Healthy Young Adults

Keywords

Physical Fatigue DetectionSurface Electromyography (sEMG)Fatigue MonitoringWearable SensorsBiosignal AnalysisElectroenchephalography (EEG)Heart rate (HR)

Outcome Measures

Primary Outcomes (3)

  • EEG (Electroencephalography) Alpha, Beta, Delta, and Theta Band Frequency (Hz)

    Relative power in the alpha (8 to 12 Hz), beta (12 to 30 Hz), delta (2 to 4 Hz), and theta (4 to 8 Hz) bands extracted from EEG signals recorded during exercise. Alpha power is associated with the onset of physical fatigue and is computed using MATLAB.

    Two sessions: Day 1 (Cycling session) and Day 2 (Squat session)

  • sEMG (Surface Electromyography) amplitude (μV) and median frequency (MDF) (Hz)

    sEMG (microvolts) recorded from both sides of the quadriceps, hamstrings, tibialis anterior, and gastrocnemius muscles. Signal processing will be performed to compute amplitude and median frequency, assessing neuromuscular activation and fatigue during exercise.

    Two sessions: Day 1 (Cycling session) and Day 2 (Squat session)

  • Heart rate (HR) and Heart rate variability (HRV)

    Heart rate (HR) and heart rate variability (HRV) are recorded in beats per minute (bpm) throughout cycling and squat sessions. Average and peak heart rates, as well as average heart rate variability (HRV), are used to evaluate physical fatigue and cardiovascular stress.

    Day 1 (Cycling session) and Day 2 (Squatting session)

Secondary Outcomes (3)

  • Body mass index (BMI)

    Two times: before and after exercise sessions

  • Static muscle strength (N)

    Two times: before and after exercise sessions

  • Borg rate of perceived exertion score (RPE)

    Two sessions: Day 1 (Cycling session) and Day 2 (Squat session)

Study Arms (1)

Single Group Protocol

EXPERIMENTAL

Participants in this arm will perform two physical exercises on different days while wearing sensors that measure muscle activity (sEMG), brain activity (EEG), and heart rate (HR).

Other: Fatigue Exercise Protocol with Biosignal Monitoring

Interventions

Fatigue Exercise Protocol with Biosignal MonitoringOTHER

Participants will complete two fatiguing exercises, including static bicycling and dumbbell squats. During each exercise, surface electromyography (sEMG), electroencephalography (EEG), and heart rate (HR) will be recorded to analyze fatigue levels.

Single Group Protocol

Eligibility Criteria

Age18 Years - 30 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64)

You may qualify if:

  • Individuals between 18 and 30 years old
  • Healthy college students who regularly exercise
  • Participants who meet the World Health Organization (WHO) guidelines for physical activity: at least 150-300 minutes of aerobic activity per week or muscle-strengthening exercises for major muscle groups on 2 or more days per week
  • Participants who provide written informed consent

You may not qualify if:

  • Individuals younger than 18 or older than 30
  • History of any metabolic, systemic, or musculoskeletal disorder
  • Recent injury or surgery
  • Failure to pass the pre-exercise fitness screening questionnaire (PAR-Q)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

National Taipei University, Master Program in Smart Healthcare Management

New Taipei City, 237303, Taiwan

Location

Related Publications (6)

  • Chen YL, Chen CC, Hsia PY, Lin SK. Relationships of Borg's RPE 6-20 scale and heart rate in dynamic and static exercises among a sample of young Taiwanese men. Percept Mot Skills. 2013 Dec;117(3):971-82. doi: 10.2466/03.08.PMS.117x32z6.

    PMID: 24665812BACKGROUND

  • Buzsaki, G. (2006). Rhythms of the Brain: Oxford university press

    BACKGROUND

  • Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, Carty C, Chaput JP, Chastin S, Chou R, Dempsey PC, DiPietro L, Ekelund U, Firth J, Friedenreich CM, Garcia L, Gichu M, Jago R, Katzmarzyk PT, Lambert E, Leitzmann M, Milton K, Ortega FB, Ranasinghe C, Stamatakis E, Tiedemann A, Troiano RP, van der Ploeg HP, Wari V, Willumsen JF. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020 Dec;54(24):1451-1462. doi: 10.1136/bjsports-2020-102955.

    PMID: 33239350BACKGROUND

  • Borghini G, Vecchiato G, Toppi J, Astolfi L, Maglione A, Isabella R, Caltagirone C, Kong W, Wei D, Zhou Z, Polidori L, Vitiello S, Babiloni F. Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:6442-5. doi: 10.1109/EMBC.2012.6347469.

    PMID: 23367404BACKGROUND

  • Bedo BLS, Pereira DR, Moraes R, Kalva-Filho CA, Will-de-Lemos T, Santiago PRP. The rapid recovery of vertical force propulsion production and postural sway after a specific fatigue protocol in female handball athletes. Gait Posture. 2020 Mar;77:52-58. doi: 10.1016/j.gaitpost.2020.01.017. Epub 2020 Jan 21.

    PMID: 31986376BACKGROUND

  • Adeel M, Chen HC, Lin BS, Lai CH, Wu CW, Kang JH, Liou JC, Peng CW. Oxygen Consumption (VO2) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises. Int J Environ Res Public Health. 2022 Feb 16;19(4):2233. doi: 10.3390/ijerph19042233.

    PMID: 35206420BACKGROUND

Study Officials

  • Muhammad Adeel, PhD

    National Taipei University

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
SCREENING
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Muhammad Adeel, DPT, Ph.D.

Study Record Dates

First Submitted

June 17, 2025

First Posted

July 15, 2025

Study Start

March 1, 2025

Primary Completion

August 31, 2025

Study Completion

November 30, 2025

Last Updated

April 13, 2026

Record last verified: 2026-04

Data Sharing

IPD Sharing
Will not share

Locations

TW(1)