Experiments/Physical Gesture Analysis

Source Paper

Using AI Algorithms and Machine Learning in the Analysis of a Bio-Purification Method (Therapeutic Emesis, Known as “Vamana Karma”): Protocol for a Mixed Methods Study

Rani P, Kalra S, Singh S, David R, Gupta AR et al.

JMIR Res Protoc • 2026

PMC

Physical Gesture Analysis

behavioralHumanN/A

Objective: AI-based framework for objective assessment of physical gestures, facial expressions, and hand/eye movements during vamana karma (therapeutic emesis) in Ayurveda

This is a Physical Gesture Analysis protocol using Human as the model organism. The procedure involves 6 procedural steps, 3 equipment items, 4 materials. Extracted from a 2026 paper published in JMIR Res Protoc.

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Replication Essentials

Model and subjects

Human • N/A • Not specified • 18-65 years • 50

Study window

~1.2 hours hands-on

Core workflow

Camera positioning and setup • Video data capture • Frame extraction and annotation

Primary readouts

Facial expression detection accuracy (disgust, sadness, tiredness, anger)
Physical gesture analysis (hand and eye movements)
Temporal correlation of emesis patterns and patient responses
Frame-level accuracy for gesture identification

Key equipment and reagents

High-definition camerasStandardized artificial lighting

Before You Start

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Protocol Steps

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Camera positioning and setup

Position high-definition cameras at forehead level facing the participant with standardized artificial lighting and monochromatic green backdrop

Not specified

View evidence from paper

“High-definition cameras (minimum 1080p resolution) will be positioned at forehead level facing the participant”

Video data capture

Record video throughout the vamana karma procedure to capture vomitus events, facial expressions, and physical gestures

approximately 70 minutes each

View evidence from paper

“Video data will be captured throughout the procedure to record vomitus events, facial expressions, and physical gestures”

Frame extraction and annotation

Process video data through frame extraction and manual annotation to create labeled datasets

Not specified

View evidence from paper

“Video data will be processed through frame extraction and manual annotation”

Facial expression analysis

Analyze patients' facial gestures by mapping various features of the face such as eyebrows, eyes, and mouth to emotions of anger, fear, surprise, sadness, and happiness

Not specified

View evidence from paper

“The patients' facial gestures will be analyzed by mapping various features of the face, such as the eyebrows, eyes, and mouth, to the emotions of anger, fear, surprise, sadness, and happiness”