Revisiting "Recognizing Human Activities User- Independently on Smartphones Based on Accelerometer Data" - What Has Happened Since 2012?

Our article “Recognizing human activities user-independently on smartphones based on accelerometer data” was published in the International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) in 2012. In 2018, it was selected as the most outstanding article published in the 10 years of IJIMAI life. To celebrate the 10th anniversary of IJIMAI, in this article we will introduce what has happened in the field of human activity recognition and wearable sensor-based recognition since 2012, and especially, this article concentrates on introducing our work since 2012.

[1]  Juha Röning,et al.  From User-independent to Personal Human Activity Recognition Models Exploiting the Sensors of a Smartphone , 2019, ArXiv.

[2]  Juha Röning,et al.  Personal models for eHealth - improving user-dependent human activity recognition models using noise injection , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

[3]  Barbara Hammer,et al.  Incremental learning algorithms and applications , 2016, ESANN.

[4]  Juha Röning,et al.  Experiences with Publicly Open Human Activity Data Sets - Studying the Generalizability of the Recognition Models , 2018, ICPRAM.

[5]  Heiko Wersing,et al.  Choosing the best algorithm for an incremental on-line learning task , 2016, ESANN.

[6]  Juha Röning,et al.  Recognizing Human Activities User-independently on Smartphones Based on Accelerometer Data , 2012, Int. J. Interact. Multim. Artif. Intell..

[7]  Vasant Honavar,et al.  Learn++: an incremental learning algorithm for supervised neural networks , 2001, IEEE Trans. Syst. Man Cybern. Part C.

[8]  Juha Röning,et al.  OpenHAR: A Matlab Toolbox for Easy Access to Publicly Open Human Activity Data Sets , 2018, UbiComp/ISWC Adjunct.

[9]  Juha Röning,et al.  Ready-to-use activity recognition for smartphones , 2013, 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

[10]  Juha Röning,et al.  Personalizing human activity recognition models using incremental learning , 2019, ESANN.

[11]  Johannes Peltola,et al.  Activity classification using realistic data from wearable sensors , 2006, IEEE Transactions on Information Technology in Biomedicine.

[12]  Paul J. M. Havinga,et al.  Fusion of Smartphone Motion Sensors for Physical Activity Recognition , 2014, Sensors.

[13]  Motoaki Kawanabe,et al.  Machine Learning in Non-Stationary Environments - Introduction to Covariate Shift Adaptation , 2012, Adaptive computation and machine learning.

[14]  Juha Röning,et al.  Using Sleep Time Data from Wearable Sensors for Early Detection of Migraine Attacks , 2018, Sensors.

[15]  K. Aminian,et al.  Physical activity monitoring based on accelerometry: validation and comparison with video observation , 1999, Medical & Biological Engineering & Computing.

[16]  Kristof Van Laerhoven,et al.  What shall we teach our pants? , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[17]  James Church,et al.  Wearable sensor badge and sensor jacket for context awareness , 1999, Digest of Papers. Third International Symposium on Wearable Computers.

[18]  Pekka Siirtola.  Recognizing Human Activities Based on Wearable Inertial Measurements - Methods and Applications , 2015, Int. J. Interact. Multim. Artif. Intell..