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Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran
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- Principal and Professor, Senior Software Engineer, Secure Connection: Cybersecurity, Senior Data Engineer, Department of Electrical Communication Engineering, Indira Institute of Technology and Sciences, Markapur, Tech Lead at Medallia, Austin, Site Reliability Engineer II (SRE) at Dell EMC | CKAD | AWS CSAA, Austin, CVS Health Centre, Dallas, Andhra Pradesh, Texas, Texas, Texas, India, United States, United States, United States
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Abstract
nThis paper investigates the integration of biosensors as innovative solutions for optimizing family dynamics and promoting mental health and well-being in the digital era. By exploring the intersection of biosensor technology with family interactions, communication patterns, and conflict resolution strategies, this study offers practical insights and recommendations for leveraging biosensors to strengthen familial relationships and support individual mental health. Through a multidisciplinary approach combining psychology, sociology, and biosensor engineering, this paper provides actionable strategies for harnessing biosensor data to enhance family cohesion, resilience, and overall well-being in the context of modern technology-mediated family life.
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Keywords: Biosensors, family dynamics, mental health, well-being, digital age, communication, conflict resolution, resilience, technology integration
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Communication Engineering & Systems(joces)]
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References
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- Haghayegh, S., Khoshnevis, S., Smooke, M. H., Dougherty, A., & Knoops, B. (2019). Wearable biosensors for monitoring health status and facilitating health behaviors. SLAS Technology, 24(4), 310-324. https://doi.org/10.1177/2472630319860466
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- Sano, A., & Picard, R. W. (2013). Stress recognition using wearable sensors and mobile phones. In 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (pp. 671-676). IEEE. https://doi.org/10.1109/ACII.2013.117
- Channa, A., & Popescu, M. (2021). Wearable biosensors for monitoring stress and emotional states: A review of machine learning techniques. Sensors, 21(18), 6030. https://doi.org/10.3390/s21186030
- Mohr, D. C., Zhang, M., & Schueller, S. M. (2017). Personal sensing: Understanding mental health using ubiquitous sensors and machine learning. Annual Review of Clinical Psychology, 13, 23-47. https://doi.org/10.1146/annurev-clinpsy-032816-044949
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- Kuzminov, R. A., & Shcherbina, A. M. (2019). Biosensor-assisted family interventions for promoting healthy lifestyles: A pilot study. Journal of Family Psychology, 33(5), 567-575. https://doi.org/10.1037/fam0000525
- Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679. https://doi.org/10.1177/2053951716679679
- Arora, S., Yttri, J., & Nilse, W. (2014). Privacy and security in mobile health (mHealth) research. Alcohol Research: Current Reviews, 36(1), 143-151.
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| Volume | 14 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 01 | |
| Received | March 25, 2024 | |
| Accepted | March 29, 2024 | |
| Published | April 5, 2024 |
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