# RFID RSS Fingerprinting System for Wearable Human Activity Recognition
## 1 Introduction
However, the performance of the system suffers from false alarm with 35% of the alarm being false [16]. [PERSON] et al. proposed an unobtrusive e-health monitoring system using several monitoring devices and sensors for monitoring a patient cardiovascular disease during sleep [17]. [PERSON] et al. proposed a smart e-health monitoring system architecture capable of monitoring, ocalizat and sharing mobile patient data with medical experts [18]. [PERSON] et al. proposed a monitoring system for acquiring the medical and contextual data of the patient's automated home [19]. [PERSON] et al. proposed an e-inclusive health system to track patients with mild dementia [20]. [PERSON] et al., [PERSON] et al. and [PERSON] et al. employed the video-based approach to track the vital signs including heart measurement rate based on facial analysis, home fitness exercise and sleep monitoring and physical activity of patients [21, 22, 23]. [PERSON] et al. explored the use of modern interactive games as a means to track and improve the physical and mental health of elderly patients [24]. Furthermore, the development of smart home as a means to track the physical and health condition of patients has also been explored. [PERSON] et al. proposed the ambient human activity recognition approach using passive radio frequency identification (RFID) tags to unobtrusively sampled target activities [25, 26]. [PERSON] et al. proposed an intelligent furniture network for human posture and activity detection [27]. [PERSON] et al. proposed and implemented a monitoring system of a smart home system for disabled people, including those with visual and hearing impairments, activating a warning against indoor accidents using mobiles phones and a wireless sensor network [28]. [PERSON] et al. proposed a smart bedroom, which monitors the daily activities for the elderly using Kinect, a camera which can detect a human body and voice movements and warns the elderly before falling out bed by controlling the electric devices in a timely manner [29]. Nevertheless, with the continuous demand for high return on investment on technological systems, the development of a simple, cost-effective wearable approach for reliable patient tracking becomes a critical design requisite. In the present work, a cost-effective target tracking system useful for monitoring the elderly, vulnerable and persons with disability is proposed. The proposed methodology is based on processing data received from low-cost RFID tags mounted on ordinary clothing using the radio frequency fingerprinting technique. Radio fingerprinting using different indoor and outdoor technologies has been used for many applications including broadcasting, location-based applications, high precision applications and activity recognition [30; 31; 32; 33; 34]. However, to the best of the authors' knowledge, the proposed system would be first that uses RFID fingerprinting methodology for inferring the patient position and orientation in real-time. The objective of the present work is to develop a cost-effective, daily human activity recognition using the RSS fingerprinting method. The proposed approach serves as an efficient automated alarming system in nursing homes, as patient inactivity or stationary position over an extended period of time would trigger the attention of nursing staffs. The paper is structured as follows: In Section 2, a detailed description of the methodology employed in the present work and the formulation of the received signal strength indicator (RSSI) model are presented. In Section 3, the performance of the Euclidean distance algorithm is evaluated using different performance metrics for all sampled activities of daily living (ADL). Section 4 concludes the findings of the present study.