Akademik Veri Yönetim Sistemi
2023 IEEE International Conference on Big Data, BigData 2023, Sorrento, İtalya, 15 - 18 Aralık 2023, ss.4973-4978
Due to the health data privacy issues, wearable devices are less useful in the industry and can not reflect their potential power. Besides, wearable health devices bring constraints such as limited energy budget, needs to recharge and impact on daily activities. To recover these problems and fulfill healthcare needs, the recent trends in the literature is to use wireless signal to capture/recognize human activities. When human activity and emotion recognition study fields merging with the machine learning techniques, can offer a innovative systems. In recent years, with the help of wireless sensing mechanisms, this study field have gained more importance. So that, these wireless sensing mechanisms have eliminated the requirement of physical body contact such as sensor devices. Nowadays, wireless sensing technologies are preferred with the easy and cost-effective access to off-the-shelf WiFi-enabled devices. In this research, a human activity and emotion recognition system have proposed with usage of WiFi channel state information(CSI) mechanism that modelled by machine learning algorithms. As a result, with a tolerable error rate, it is possible to distinguish person's heart rate information with a contactless solution via wi-fi signal.