Smartwatch as a Pervasive Computing Application in Health Metrics Tracking
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In smartwatches and fitness trackers, TLMs support real-time natural language interactions, allowing users to query health metrics such as heart rate, activity levels, or sleep quality.
“In smartwatches and fitness trackers, TLMs support real-time natural language interactions, allowing users to query health metrics such as heart rate, activity levels, or sleep quality [143,144].”
From Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions (2025) · cites this paper as [143]
Cites
Decoupling computation and data scheduling in distributed data-intensive applications
Ranganathan, K. L., & Foster, I. T. (2003) · IEEE International Symposium on High Performance Distributed Computing (HPDC) · doi:10.1109/hpdc.2002.1029935 · Cited by 464 · see citing works
Towards pervasive computing in health care – A literature review
Orwat, C., Graefe, A., & Faulwasser, T. (2008) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-8-26 · Cited by 232 · see citing works
Smartwatch-based activity recognition: A machine learning approach
Weiss, G. M., Timko, J. L., Gallagher, C. M., Yoneda, K., & Schreiber, A. J. (2016) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi.2016.7455925 · Cited by 209 · see citing works
Controlling Home and Office Appliances with Smart Phones
Nichols, J. W., & Myers, B. A. (2006) · IEEE Pervasive Computing · doi:10.1109/mprv.2006.48 · Cited by 118 · see citing works
Designing a Smart and Intelligent Ecosystem for Autistic Children
Sen, M., Sharma, K., Mishra, S., et al. (2023) · International Conference on Intelligent Engineering and Management (ICIEM) · doi:10.1109/iciem59379.2023.10166057 · Cited by 45 · see citing works
Self-citationUniversal Interactions with Smart Spaces
Lee, C., Helal, S., & Lee, W. (2006) · IEEE Pervasive Computing · doi:10.1109/mprv.2006.19 · Cited by 31 · see citing works
A Smart Data-Driven Prototype for Depression and Stress Tracking in Patients
Pranjal, P., Mallick, S., Madan, M., Mishra, S., Alkhayyat, A. H., & Bhaktisudha, S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-3010-4_36 · Cited by 31 · see citing works
Self-citationROAMM: A software infrastructure for real-time monitoring of personal health
Nair, S., Kheirkhahan, M., Davoudi, A., et al. (2016) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom.2016.7749479 · Cited by 25 · see citing works
The Multiple Dispositions of On-Body and Wearable Devices
Lyons, K., & Profita, H. P. (2014) · IEEE Pervasive Computing · doi:10.1109/mprv.2014.79 · Cited by 22 · see citing works
Actigraphy features for predicting mobility disability in older adults
Kheirkhahan, M., Tudor-Locke, C. E., Axtell, R. S., Buman, M. P., Fielding, R. A., Glynn, N. W., Guralnik, J. M., King, A. C., White, D. K., Miller, M. E., et al. (2016) · Physiological Measurement · doi:10.1088/0967-3334/37/10/1813 · Cited by 18 · see citing works
Validation of a Commercial Android Smartwatch as an Activity Monitoring Platform
Amor, J. D., & James, C. J. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2732678 · Cited by 12 · see citing works
Chakraborty, S., & Mishra, S. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-8763-1_58 · Cited by 11 · see citing works
Self-citationComparative Analysis of Breast Cancer Diagnosis Driven by the Smart IoT-based Approach
Mittal, B., Sharma, P., Mishra, S., et al. (2023) · River Publishers eBooks · doi:10.1201/9781032629353-17 · Cited by 9 · see citing works
Self-citationPower-efficient real-time approach to non-wear time detection for smartwatches
Kheirkhahan, M., Das, H., Battula, M., Davoudi, A., Rashidi, P., Manini, T. M., & Ranka, S. (2017) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi.2017.7897244 · Cited by 6 · see citing works
Faiez, H., & Akaichi, J. (2016) · Journal of Software · doi:10.17706/jsw.11.11.1119-1131 · Cited by 2 · see citing works
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Lamaakal, I., Maleh, Y., El Makkaoui, K., Ouahbi, I., Pławiak, P., Alfarraj, O., Almousa, M., & Abd El-Latif, A. A. (2025) · Sensors · doi:10.3390/s25051318 · Cited by 60 · see citing works
- Authors
- Sah, A., Saurav, S., Meena, A., Mishra, S., & Kumar, N.
- Affiliations
- KIIT University (IN)
- University of Nizwa (OM)
- Corresponding author
- Mishra, Sushruta
- Venue
- Lecture Notes in Networks and Systems
- Publisher
- Springer Nature Singapore
- Published
- 2024-10-15
- Pages
- 145-157
- ISSN
- 2367-3370 (ISSN-L)
- 2367-3389
- OpenAlex
- W4403371903
- Cited by
- 15
- References
- 16
- Citations by year
- 2026: 2 · 2025: 13
- FWCI
- 14.13
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Lecture notes in networks and systems (publishedVersion, public-domain)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- smartwatches, ubiquitous computing, wearable health monitoring, heart rate monitoring, sleep monitoring, physical activity monitoring, telemedicine, remote patient monitoring, personalized healthcare, mental health, wellness
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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