Medicinal prescription by professionals depends on not just the lab reports of the patient but also on the physical examination of the patient. The inability of AI to recognize pain and express empathy has been a significant factor of its limited use in actual real-life diagnosis.
Doctor examines a patient. Image credit: Pixabay, CC0 Public Domain via Stockvault
The ability of AI to identify pain and express empathy has been discussed in the research paper by Siqi Cao, Di Fu, Xu Yang, Pablo Barros, Stefan Wermter, Xun Liu, and Haiyan Wu titled “How Can AI Recognize Pain and Express Empathy?” which forms the basis of the following text.
Importance of this Research
AI can be an excellent aid for medical professionals in diagnosing patients and prescribing accurate medicines. It will help us treat patients in the best possible way: lab report analysis, physical examination, and mental health therapy. Should we be able to recognize pain and express empathy to patients via an AI algorithm, it would help us create the “Perfect Doctor” in a digital form.
The objective of this Research
This research paper aims to review the current developments for computational pain recognition and artificial empathy implementation.
The research paper notes that the clinical evaluations could be inaccurate due to a variety of reasons. For example, some patients could be overlooked, or there could be a linguistic gap between the patient and the doctor etc. In some cases, it could also depend on the mental state of the patient. Patient care is a critical area, and hence it has been an area of great interest for researchers.
Image credit: arXiv:2110.04249 [cs.AI]
Pain recognition can be identified by AI using the below 3 techniques
- Facial Expression
- Speech
- Gesture
Pain recognition could also be multimodal in nature that uses a combination of tools available.
An example of multimodal pain recognition. Image credit: arXiv:2110.04249 [cs.AI]
Pain Recognition can be further improved by
- Analyzing Memory System: For example, patients’ pain sensitivity is unique & analyzing patients history could be helpful to identify pain much effectively.
- Analyzing Social contexts & Environment: Patients might react differently in different social settings.
- Establishing Weight of expression: This considers that people might have their preferred modes of pain expression: speech versus facial expression versus gesture.
The challenges in multimodal pain recognition and future directions are also discussed in the research paper.
Conclusion
In the words of the researchers,
This paper highlights the potential of multimodal signals for improving pain recognition. With regular monitoring of patient pain levels by clinical staff, patients can obtain timely treatment. Notwithstanding, a computational solution as a complementary AI assistant could be helpful in certain situations. However, some outstanding challenges include noise estimation in unimodal sources, multiple feature extraction, comparison of fusion methods, and establishing balanced and compatible datasets to address the need for real-time applications.
Moreover, an AI assistant should show socially acceptable verbal and non-verbal signals to achieve positive interactions. Although AI can be empathic, its inherent limitations provide challenges regarding understanding, intention, and trust. Exploring affective AI by both psychology and computer science researchers may help to unravel how humans understand others based on sensory and emotional states. Beyond that, artificial pain empathy could enable an AI assistant to become more socially acceptable and generate positive interpersonal interaction. With the pain state analysis and human-level expressions, an artificial agent could be considered not only a binary logic device but also a helpful assistant trained to express empathy and safely interact with humans
Source: Siqi Cao, Di Fu, Xu Yang, Pablo Barros, Stefan Wermter, Xun Liu, and Haiyan Wu
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