Psychological Assistant: Assessing The Emotional State of a Patient Using Triple Video Analysis Method

The “Psychological Assistant” presents a groundbreaking approach to remote emotion assessment by integrating video analysis techniques, computer vision, speech recognition, and Natural Language Processing (NLP). Leveraging pre-trained models such as Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), and advanced NLP algorithms, the system analyzes facial expressions, voice signals, and Text Classification to provide mental health practitioners with comprehensive insights during remote consultations. Through the use of methods such as averaging and combining over time, the system ensures a thorough emotion evaluation, promising high accuracy and reliability in mood identification. This innovative integration of NLP enhances the system’s capability to understand and interpret textual cues, allowing for a more holistic assessment of patients’ mental states. The technology holds the potential for early intervention, personalized treatment plans, and an elevated standard of care in remote mental health services, representing a significant advancement in digital healthcare solutions.

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Publication Details

Published
2024-09-21
DOI
https://doi.org/10.1109/idap64064.2024.10711071
Citations
4
Primary Topic
Psychiatric care and mental health services
Type
article
Field-Weighted Citation Impact
2.56
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article

Psychological Assistant: Assessing The Emotional State of a Patient Using Triple Video Analysis Method

Mustafa Nail ALKAN, Wisam Elmasry
4 citations
Psychiatric care and mental health services
2.56
article

Psychological Assistant: Assessing The Emotional State of a Patient Using Triple Video Analysis Method

Mustafa Nail ALKAN, Wisam Elmasry
article en
4 citations

Abstract

The “Psychological Assistant” presents a groundbreaking approach to remote emotion assessment by integrating video analysis techniques, computer vision, speech recognition, and Natural Language Processing (NLP). Leveraging pre-trained models such as Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), and advanced NLP algorithms, the system analyzes facial expressions, voice signals, and Text Classification to provide mental health practitioners with comprehensive insights during remote consultations. Through the use of methods such as averaging and combining over time, the system ensures a thorough emotion evaluation, promising high accuracy and reliability in mood identification. This innovative integration of NLP enhances the system’s capability to understand and interpret textual cues, allowing for a more holistic assessment of patients’ mental states. The technology holds the potential for early intervention, personalized treatment plans, and an elevated standard of care in remote mental health services, representing a significant advancement in digital healthcare solutions.

Istanbul Kültür University (TR)
Gender equality
Openalex Percentile: Top 11%
Psychiatric care and mental health services
2.56
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Psychological Assistant: Assessing The Emotional State of a Patient Using Triple Video Analysis Method — Mustafa Nail ALKAN, Wisam Elmasry · (2024) | TGRS Research Map | TGRS