Depression AI

Wearable AI is a promising tool for depression detection and prediction although it is in its infancy and not yet ready for use in clinical practice - as concluded in a recent review. AI can be also used therapeutically. 

Research has shown that interacting with technology, such as chatbots, can lead to feelings of social connection and companionship, which can have both positive and negative effects on mental well-being. Chatbots have become increasingly popular in mental health domain because of their impact on social interactions and the ability to form and maintain meaningful relationships. They are effective in reducing symptoms of anxiety and depression, although there is always a risk that they may exacerbate mental health issues. 

One of the main benefits of chatbots is their ability to provide low-cost and easily accessible mental health counseling. ChatGPT studies show that its potential for depression detection and treatment should be further explored, while addressing the challenges and ethical considerations. ChatGPT outperforms traditional neural network methods but still has a significant gap with advanced task-specific methods. 

In the US, one in five individuals is affected by mental health issues each year, with recreational cannabis use increasing the risk. Intelligent wearables utilize over 30 types of data to predict depression, with physical activity, sleep, heart rate, and mental health measures being the most commonly used. The Depresjon dataset (motor activity recordings of 23 unipolar and bipolar depressed patients and 32 healthy controls) is most popular among researchers.

Previous systematic reviews have shown that AI has better performance in detecting patients without depression than those with depression, but the review published last week shows slightly higher sensitivity and specificity - based on data from wearable devices. It is recommended that tech companies develop wearable devices that can detect and predict depression in real-time. Neuroimaging data in addition to wearable devices would provide even higher diagnostic performance.

With the increasing popularity of IoT and AI, they will likely become an integral part of our lives.  It may soon become a useful tool in clinical practice.

REFERENCES

Abd-Alrazaq A, AlSaad R, Shuweihdi F, Ahmed A, Aziz S, Sheikh J. Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression. NPJ Digit Med. 2023 May 5;6(1):84. doi: 10.1038/s41746-023-00828-5. PMID: 37147384.

Garcia-Ceja E, Riegler M, Jakobsen P, Tørresen J, Nordgreen T, Oedegaard KJ, Fasmer OB. Depresjon: a motor activity database of depression episodes in unipolar and bipolar patients. In Proceedings of the 9th ACM multimedia systems conference 2018 Jun 12 (pp. 472-477).

Lamichhane B. Evaluation of ChatGPT for NLP-based Mental Health Applications. arXiv preprint arXiv:2303.15727. 2023 Mar 28. 

Yang K, Ji S, Zhang T, Xie Q, Ananiadou S. On the Evaluations of ChatGPT and Emotion-enhanced Prompting for Mental Health Analysis. arXiv preprint arXiv:2304.03347. 2023 Apr 6.

Dana RA, Gavril RA. Exploring the psychological implications of ChatGPT: a qualitative study. Journal Plus Education. 2023 May 1;32(1):43-55.