Abstract
The rapid growth in the population and the changes endured in the lifestyle of the people increases the demand for the healthcare segments that does a continuous monitoring of the heath. The artificial intelligence that has been engaged in the numerous of real-life applications, has caused a greater impact in the very basic facet of the human life such as the communication, interaction, education, driving, entertainment and has been limited to the heath monitoring. For decades it is the artificial intelligence is been utilized in the health care for the analysis and the diagnosis of the disease, for assisting the surgical methodologies etc. has also been utilized in the improving the health of the person by monitoring the quality of the sleep they have. The paper puts forth a sleep pattern analysis using the artificial intelligence and the therapy based on the music for improving the sleeping time and reducing the stress according to the quality of the sleep evaluated.
References
Carswell, William, P. J. McCullagh, Juan Carlos Augusto, Suzanne Martin, M. D. Mulvenna, H.Zheng, H. Y. Wang et al. "A review of the role of assistive technology for people with dementia in the hours of darkness." Technology and Health Care 17, no. 4 (2009): 281-304.
O'Kelly, Julian, L. James, Ramaswamy Palaniappan, J. Fachner, J. Taborin, and Wendy L. Magee. "Neurophysiological and behavioral responses to music therapy in vegetative and minimally conscious states." Frontiers in Human Neuroscience 7 (2013): 884.
WEI, ZHAO. "Utilizing EEG signal in music information retrieval." PhD diss., 2010.
Raglio, A., D. Bellandi, M. Gianotti, E. Zanacchi, M. Gnesi, M. C. Monti, C. Montomoli et al. "Daily music listening to reduce work-related stress: a randomized controlled pilot trial." Journal of Public Health (2019).
Harwood, Tracy, Elizabeta Mukaetova-Ladinska, and John Maltby. "Role of Artificial Intelligence (AI) art in care of ageing society: Focus on dementia." (2019).
McNamara, Patrick, Kelly Duffy-Deno, and Tom Marsh. "Dream content analysis using Artificial Intelligence." International Journal of Dream Research (2019): 42-52.
Papakostas, Michalis. "FROM BODY TO BRAIN: USING ARTIFICIAL INTELLIGENCE TO IDENTIFY USER SKILLS & INTENTIONS IN INTERACTIVE SCENARIOS." PhD diss., 2019.
Wagner, Jessyca B. "Artificial Intelligence in Medical Imaging." Radiologic technology 90, no. 5 (2019): 489-501.
Khojandi, Anahita, Oleg Shylo, and Maryam Zokaeinikoo. "Automatic EEG classification: a path to smart and connected sleep interventions." Annals of Operations Research 276, no. 1-2 (2019): 169-190.
Ravan, Maryam, and Jason Begnaud. "Investigating the Effect of Short Term Responsive VNS Therapy on Sleep Quality Using Automatic Sleep Staging." IEEE Transactions on Biomedical Engineering (2019).
O’Caoimh, Rónán, Helen Mannion, Duygu Sezgin, Mark R. O’Donovan, Aaron Liew, and D. William Molloy. "Non-pharmacological treatments for sleep disturbance in mild cognitive impairment and dementia: A systematic review and meta-analysis." Maturitas (2019).
Kallipolitis, A., M. Galliakis, Andreas Menychtas, and Ilias Maglogiannis. "Emotion Analysis in Hospital Bedside Infotainment Platforms Using Speeded up Robust Features." In IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 127-138. Springer, Cham, 2019.
Jensen, Elizabeth AG, Justin Smith, and Christine R. Kovach. "Social Robots, Robotic Assistants, and Home Health Monitoring Devices: A Gerontological Research Perspective." Research in gerontological nursing 12, no. 4 (2019): 163-166.