EMoCy - Emotions Monitoring via wearable Computing System
- Ana Bogdanovic, M. Sc. student in Biomedical Engineering - Lorenzo Gecchelin, M. Sc. student in Design & Engineering - Anisia Lauditi, M. Sc. student in Biomedical Engineering - Noemi Gozzi, M. Sc. student in Biomedical Engineering - Armando Bellante, M. Sc. student in Computer Science & Engineering - Letizia Bergamasco, M. Sc. student in ICT for Smart Societies - Moaad Khamlich, M. Sc. student in Computational Engineering Stress is a psycho-physical response to very different loads, of an emotional, cognitive or social nature, which is perceived as excessive thus having severe implications on wellbeing both in the short and in the long term. Different physiological manifestations occur during stressful events which, if detected promptly, can help in managing the situation. Therefore, the objective of this project is to develop a small portable device for psychological stress detection. This includes design of machine learning framework for stress detection and a prototype of a low-cost portable device for recording the physiological data. The ML framework is including the model together with the heuristic and knowledge based feature engineering from physiological time series. As a result EMoCy system is achieving accuracy of 97.2 ± 2% on stress/baseline binary classification task.
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EMoCy - Emotions Monitoring via wearable Computing System
- 1. 1 EMoCy 22nd July 2020 Team: Armando Bellante Letizia Bergamasco Ana Bodganovic Lorenzo Gecchelin Noemi Gozzi Moaad Khamlich Anisia Lauditi Supervisor: Marco Domenico Santambrogio Eleonora D’Arnese
- 2. Lorenzo Gecchelin Design & Engineering Noemi Gozzi Biomedical Engineering Armando Bellante Computer Science & Engineering Anisia Lauditi Biomedical Engineering Letizia Bergamasco ICT for Smart Societies Ana Bogdanović Biomedical Engineering Moaad Khamlich Computational Engineering Team 2
- 3. Outline Idea and Group Vision Project Outcome Future plans 3
- 5. 5 Stress
- 6. Statistics 17% Communicable, maternal, perinatal and nutritional conditions 6% Injuries 31% Mental, neurological and substance use disorders 14% Musculoskeletal diseases 31% Other non- communicable diseases (e.g. CVD, cancer, diabetes, respiratory diseases) 10% Depression 4% Anxiety disorder s 4% Alcohol use disorders 14% Other disorders Global distribution of non-fatal disease burden of disease (years lived with disability ) Mnookin, S. (2016). Out of the Shadows: Making Mental Health a Global Development Priority. [Report] World Health Organization and World Bank Group. Available at: https://www.who.int/mental_health/advocacy/wb_background_paper.pdf?ua=1 [Accessed 7 Nov. 2019]. 6
- 9. Project outcome Stress detection 9 PoC Software
- 10. PoC 1. GSR Sensor 2. PPG Sensor 3. Respiration Sensor3 2 1 10 Total cost ~ € 185,00
- 11. Software Feature Extraction (Knowledge based) Feature SelectionPreprocessing ClassificationData Feature engineering 11
- 12. Software Feature Extraction (Knowledge based) Feature SelectionPreprocessing ClassificationData Feature engineering window 1 window 2 window 3 Time series windowing 12
- 13. Software Feature Extraction (Knowledge based) Feature SelectionPreprocessing ClassificationData Feature engineering LOSO Crossvalidation Emocy SVM: 97.2% Benchmark LDA: 93.12% 13
- 14. CONSEQUENCESRESULTS less computational power reduced power consumption less sophisticated sensors better accuracy (97.2%) lower sampling frequency (64 Hz) smaller windows (60s) fewer signals (EDA, RESP, PPG) 14 Emocy - So Far
- 15. better accuracy (97.2%) lower sampling frequency (64 Hz) smaller windows (60s) fewer signals (EDA, RESP, PPG) CONSEQUENCESRESULTS less computational power reduced power consumption less sophisticated sensors WEARABLE DEVICE 15 Emocy - So Far
- 17. Plans and goals Experimental phase User Experience Market opportunities LONG TERMSHORT TERM WEARABLE DEVICE 17
- 18. Thank you Q&A Lorenzo Gecchelin Design & Engineering lorenzo.gecchelin@asp-poli.it Noemi Gozzi Biomedical Engineering noemi.gozzi@asp-poli.it Armando Bellante Computer Science & Engineering armando.bellante@asp-poli.it Anisia Lauditi Biomedical Engineering anisia.lauditi@asp-poli.it Letizia Bergamasco ICT for Smart Societies letizia.bergamasco@asp-poli.it Ana Bogdanović Biomedical Engineering ana.bogdanovic@asp-poli.it Moaad Khamlich Computational Engineering moaad.khamlich@asp-poli.it 18