A DEEP LEARNING-BASED REAL-TIME YOGA ASSISTANCE FOR THE VISUALLY IMPAIRED

Registration ID: IJNRD_220327

Published ID: IJNRD2406334

DOI: Click Here to Get

Shahana Shirin CP , Fathima PK , Fathimathul misba shareen , Fathima Zuhara PK , Ms.REMYA PV

, Mediapipe, SpeechRecognition, and CNN

Yoga offers many physical, mental, and emotional benefits, and having a trained instructor by our side can significantly enhance the experience and outcomes.Here, we’ve suggested a method that increases yoga’s accessibility and inclusivity for everybody, particularly the blind. Users can personalize their yoga experience, get real-time feedback, and even request particular exercises. The voice assistant communicates through speech-to-text and text-to-speech technologies. Using a deeplearning Convolutional Neural Network (CNN), the system is trained to predict and correct yoga positions based on key body locations. The suggested yoga posture estimate system takes advantage of the OpenPose method in MediaPipe, a popular computer vision technique for identifying and following key spots on the human body in pictures or movies. OpenPose, Mediapipe, SpeechRecognition, and CNN are index terms.

Published Paper   E-Certificate

Shahana Shirin CP, Fathima PK, Fathimathul misba shareen, Fathima Zuhara PK, & Ms.REMYA PV (June-2024). A DEEP LEARNING-BASED REAL-TIME YOGA ASSISTANCE FOR THE VISUALLY IMPAIRED. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), d406-d409. https://ijnrd.org/papers/IJNRD2406334.pdf

Volume 9 Issue 6, June-2024

Pages : d406-d409

Paper Reg. ID: IJNRD_220327

Published Paper Id: IJNRD2406334

Downloads: 000121981

Research Area: Engineering

Country: Kannur, KERALA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2406334.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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