Publication2020
Sleep and Sedentary Behavior Analysis from Physiological Signals using Machine Learning
The record
- Type
- Publication
- Date
- 1 March 2020
- Level
- National
- Journal
- 2nd International Conference on Innovative Mechanisms for Industry Applications Icimia 2020 Conference Proceedings
- Pages
- 240-244
- Published
- 1 March 2020
- DOI
- 10.1109/icimia48430.2020.9074883
- Scopus ID
- 85084525419
- Authors
- 3
- Open access
- No
- Citations
- 4
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
3 Ensure healthy lives and promote well-being for all at all ages
Wearable device physiological signal analysis with machine learning distinguishes sleep and sedentary behavior
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Wearable technology monitoring supports personal health awareness and sedentary behavior reduction
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Sleep and Sedentary Behavior Analysis from Physiological Signals using Machine Learning”. Kortex.