Stress Detection in Classroom Environment Using Physiological Data

Author:

Sharada A.ORCID,Ratkal BhageshwariORCID,Lalitha M.ORCID,Samhitha K. N. V.,Rishika Reddy A.

Publisher

Springer Nature Singapore

Reference8 articles.

1. Gjoreski H, Kozina S, Gams M, Luštrek M, Álvarez-García JA, Hong JH, Ramos J, Dey AK, Bocca M, Patwari N (2015) Competitive live evaluation of activity-recognition systems. IEEE Pervasive Comput 14(1):70–77

2. Sharada A (2020) Machine learning approach for stress detection using bio signals, robotics design and applications using wireless sensor networks, IoT & AI. IFERP

3. Gjoreski H, Kalužaa B, Gams M, Milić R, Luštrek M (2015) Context-based ensemble method for human energy expenditure estimation. Appl Soft Comput 37:960–970

4. Siirtola P, Koskimäki H, Röning J (2018) Personalising human activity recognition models using incremental learning. In: European symposium on artificial neural networks, computational intelligence and machine learning (ESANN), pp 627–632, Apr 2018

5. Incel O, Kose M, Ersoy C (2013) A review and taxonomy of activity recognition on mobile phones. Bio Nano Sci 3(2):145–171

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