The Effect of an AIoT-Based Smart Exercise System in Older Adults

NCT07779824 | Recruiting

• 1 other identifier: EMRP-114-162A
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

This clinical trial aims to evaluate the effectiveness of an artificial intelligence of things (AIoT)-based exercise system for seniors. Participants will undergo a 12-week AIoT-based cycle ergometer training program. Physical fitness and functional performance will be assessed at baseline and after completion of the intervention. Throughout the intervention, exercise-related data, including exercise duration, workload, heart rate, oxygen consumption, perceived exertion, and facial expressions, will be continuously and simultaneously collected for analysis.

Conditions

Exercise; Seniors

Keywords

Seniors; Exercise; facial action unit

Outcome Measures

Primary Outcomes (2)

• 30 second chair stand test

  Number of full stands that can completed in 30 seconds with arms folded across chest.

  baseline

• 30 second chair stand test

  Number of full stands that can be completed 30 seconds with arms folded across chest.

  Within 7 days after completion of the 12-week intervention

Secondary Outcomes (29)

• BMI

  baseline

• BMI

  Within 7 days after completion of the 12-week intervention

• Up and Go test

  baseline

• Up and Go test

  Within 7 days after completion of the 12-week intervention

• Six-minute walk test

  baseline

Study Arms (1)

AIoT-based Exercise

EXPERIMENTAL

Seniors participants will undergo a 12-week AIoT-based cycle ergometer exercise program.

Device: AIoT-based cycle ergometer exercise system

Interventions

AIoT-based cycle ergometer exercise system DEVICE

AIoT-based cycle ergometer exercise system The system also continuously records exercise-related device data, personal physiological parameters, and facial action units in a structured and systematic manner.

AIoT-based Exercise

Eligibility Criteria

• Age: 50 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adult over 50 years old
• No significant limb disability or joint deformation
• No history of cardiovascular disease
• Never lost balance due to dizziness in the past 12 months

You may not qualify if:

• Limb disability or joint deformation
• History of cardiovascular disease
• Lost balance due to dizziness in the past 12 months
• Cognitive deficits

Sponsors & Collaborators

• I-Shou University: lead
• National Cheng-Kung University Hospital: collaborator

Study Sites (1)

I-Shou University

Kaohsiung City, 824, Taiwan

RECRUITING

MeSH Terms

Conditions

Motor Activity

Condition Hierarchy (Ancestors)

Behavior

Central Study Contacts

Chih-Chun Lin

CONTACT

+886-76151100 Ext. 7566; chihchunlin@isu.edu.tw

Chien-Yu Hsu

CONTACT

+886-76151100 Ext. 7597; sophia992104@isu.edu.tw

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor

Study Record Dates

• First Submitted: August 14, 2026
• First Posted: August 21, 2026
• Study Start: February 20, 2026
• Primary Completion (Estimated): July 31, 2028
• Study Completion (Estimated): July 31, 2028
• Last Updated: August 26, 2026

Record last verified: 2026-08

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)