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CTRI Number  CTRI/2024/10/075513 [Registered on: 18/10/2024] Trial Registered Prospectively
Last Modified On: 18/10/2024
Post Graduate Thesis  Yes 
Type of Trial  Interventional 
Type of Study   Diagnostic
Preventive
Screening
Physiotherapy (Not Including YOGA) 
Study Design  Cluster Randomized Trial 
Public Title of Study   Pulse rate based device to guide fitness enthusiasts to perform exercises correctly  
Scientific Title of Study   Al-enabled pulse rate based biofeedback device to guide fitness enthusiasts in performing exercises correctly 
Trial Acronym  NIL 
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Rajvi Divyeshbhai Kamdar 
Designation  Post Graduate Student 
Affiliation  School Of Physiotherapy, RK University 
Address  Research Department, Room no. 207, School of Physiotherapy, RK University kasturbadham Rajkot-Bhavnagar Highway

Rajkot
GUJARAT
360020
India 
Phone  9408814088  
Fax    
Email  rkamdar609@rku.ac.in  
 
Details of Contact Person
Scientific Query  
Name  Prof Dr Priyanshu V Rathod  
Designation  Professor, School of Physiotherapy, Dean, Faculty of Medicine, RK University. 
Affiliation  School Of Physiotherapy, RK University 
Address  Research Department, Room no. 207, School of Physiotherapy, RK University kasturbadham Rajkot-Bhavnagar Highway

Rajkot
GUJARAT
360020
India 
Phone  9426803108  
Fax    
Email  priyanshu.rathod@rku.ac.in  
 
Details of Contact Person
Public Query  
Name  Prof Dr Priyanshu V Rathod  
Designation  Professor, School of Physiotherapy, Dean, Faculty of Medicine, RK University. 
Affiliation  School Of Physiotherapy, RK University 
Address  Research Department, Room no. 207, School of Physiotherapy, RK University kasturbadham Rajkot-Bhavnagar Highway

Rajkot
GUJARAT
360020
India 
Phone  9426803108  
Fax    
Email  priyanshu.rathod@rku.ac.in  
 
Source of Monetary or Material Support  
School Of Physiotherapy, RK University, Rajkot 360020, India 
 
Primary Sponsor  
Name  School of Physiotherapy, RK University 
Address  Kasturbadham, Rajkot-Bhavnagar Highway, Rajkot, Gujarat, India 
Type of Sponsor  Research institution and hospital 
 
Details of Secondary Sponsor  
Name  Address 
RAJVI DIVYESHBHAI KAMDAR   School of Physiotherapy, RK University, Kasturba Dham, Rajkot-Bhavnagar Highway, Rajkot, Gujarat, India 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 1  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Dr Rajvi Divyeshbhai Kamdar  School Of Physiotherapy  Research Department, Room no. 207, School of Physiotherapy, RK University kasturbadham Rajkot-Bhavnagar Highway
Rajkot
GUJARAT 		 9408814088

rkamdar609@rku.ac.in 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Institutional Ethical Committee, School of Physiotherapy, RK University,  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Healthy Human Volunteers  Healthy individuals according to SF-36 questionnaire  
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  AI-Enabled Pulse Rate Biofeedback device  This intervention utilizes a wearable wristband that monitors pulse rate, rhythm, and flow during exercise, providing real-time biofeedback through auditory or visual cues based on the Rate of Perceived Exertion (RPE). The total duration of this intervention will be 1 month. 
Comparator Agent  the Rate of Perceived Exertion (RPE)  Before developing the algorithm, the Rate of Perceived Exertion (RPE) will be assessed to identify its association with age, gender, pulse (rate, rhythm, and flow), and exercise intensity. Subsequently, RPE will be used as a verification tool to monitor changes in these parameters and adjust exercise intensity accordingly. 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  65.00 Year(s)
Gender  Both 
Details  Screening with SF-36 Health Questionnaire
 
 
ExclusionCriteria 
Details  1. Pregnancy
2. Recent Surgery or Injury in last 6 months
3. History of hospitalization in the last 6 months
 
 
Method of Generating Random Sequence   Adaptive randomization, such as minimization 
Method of Concealment   An Open list of random numbers 
Blinding/Masking   Participant Blinded 
Primary Outcome  
Outcome  TimePoints 
1. Harvard Step Test
2. Rate of Perceived Exertion (RPE)
3. Radial Pulse – Rate, rhythm and flow
 		 1. Before the exercise performance
2. During the exercise performance
3. After the exercise performance  
 
Secondary Outcome  
Outcome  TimePoints 
Exercise efficiency & performance  Continuous monitoring while performing exercise  
Reduction in injury risk  History of injuries in last 6 months & upcoming 1 month, 3 months & 6 months  
 
Target Sample Size   Total Sample Size="60"
Sample Size from India="60" 
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" 
Phase of Trial   N/A 
Date of First Enrollment (India)   01/01/2025 
Date of Study Completion (India) Applicable only for Completed/Terminated trials 
Date of First Enrollment (Global)  Date Missing 
Date of Study Completion (Global) Applicable only for Completed/Terminated trials 
Estimated Duration of Trial   Years="0"
Months="4"
Days="0" 
Recruitment Status of Trial (Global)   Not Applicable 
Recruitment Status of Trial (India)  Not Yet Recruiting 
Publication Details   N/A 
Individual Participant Data (IPD) Sharing Statement

Will individual participant data (IPD) be shared publicly (including data dictionaries)?  

Response - NO
Brief Summary   Title: AI-ENABLED PULSE RATE-BASED BIOFEEDBACK DEVICE TO GUIDE FITNESS ENTHUSIASTS IN PERFORMING EXERCISES CORRECTLY
 
Background: Exercise is an integral part of health and wellness. For optimal health benefits and injury prevention, individuals must understand their individual exercise thresholds (such as anaerobic threshold) in relation to various exercise intensities, including walking, running on a treadmill, and weight lifting. Self-analysis and control of exercise intensity help achieve fitness goals while preventing excessive strain on the body. However, it is challenging for individuals to closely monitor their exertion levels and maintain them within safe limits. A Pulse Rate-based AI-enabled Biofeedback device can address this need by providing real-time monitoring and feedback, thus preventing critical challenges to the physiological system.
 
Need of the study: 
1. Monitoring Exertion Levels with Real-time Biofeedback.
2. Understanding Exercise Thresholds and performing submaximal exercises. 
3. Identifying and understanding the progression of Exercises. 

Research problem: The primary research problem addressed by this study is individuals’ difficulty in accurately monitoring their exertion levels and maintaining them within safe limits during exercise. Current fitness monitoring devices often lack real-time feedback and fail to provide personalized insights into exercise thresholds, resulting in submaximal workouts and increased injury risk. There is a need for an advanced, AI-enabled biofeedback device that offers real-time monitoring and feedback based on pulse rate, rhythm, and flow. This device will help users stay within their exercise thresholds, improve performance, reduce injury risk, and increase satisfaction compared to traditional self-monitoring methods.

Aim: This study aims to develop and validate an algorithm for  the rate, rhythm, and flow of the radial pulse which is taken by an AI-enabled pulse rate-based biofeedback device

Objectives:  

1. Evaluate the accuracy of an AI-enabled biofeedback device in predicting and maintaining exercise intensity within the optimal threshold, as measured by pulse rate, rhythm, and flow, compared to the actual Rate of Perceived Exertion (RPE).
2. Assess the impact of the AI-enabled biofeedback device on exercise efficiency and performance.
3. Determine the effectiveness of the AI-enabled biofeedback device in reducing injury risk during exercise.

Methods: Efficacy Testing  of AI-enable pulse rate-based biofeedback device: - (Two stages) This phase has two stages, 
Stage 1: Exercise Data Analysis and Algorithm Development: Thirty healthy individuals will perform the Harvard Step Test at moderate intensity (RPE 13), with their exercise intensity, pulse rate, and step-up count recorded to develop an algorithm. Blood samples will be taken at moderate intensity to validate anaerobic threshold biomarkers. 
Stage 2: Algorithm Evaluation and Accuracy Testing: The developed algorithm will be tested on a new set of 30 individuals to reach moderate intensity (RPE 13). The actual RPE will be recorded and correlated with the algorithm-predicted RPE to evaluate accuracy.
 
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