The emerging wearable medical devices open up new opportunities for the provision of health services and promise to accelerate the development of novel telemedical services. The main objective of this study was to investigate the desirable features and applications of telemedical services for the Polish older adults delivered by wearable medical devices. https://doi.org/10.3390/s20185181

This paper presents a multimodal system for seamless surveillance of elderly people in their living environment. The system uses simultaneously a wearable sensor network for each individual and premise-embedded sensors specific for each environment. The paper demonstrates the benefits of using complementary information from two types of mobility sensors: visual flow-based image analysis and an accelerometer-based wearable network. The paper provides results for indoor recognition of several elementary poses and outdoor recognition of complex movements. Instead of complete system description, particular attention was drawn to a polar histogram-based method of visual pose recognition, complementary use and synchronization of the data from wearable and premise-embedded networks and an automatic danger detection algorithm driven by two premise- and subject-related databases. The novelty of our approach also consists in feeding the databases with real-life recordings from the subject, and in using the dynamic time-warping algorithm for measurements of distance between actions represented as elementary poses in behavioral records. The main results of testing our method include: 95.5% accuracy of elementary pose recognition by the video system, 96.7% accuracy of elementary pose recognition by the accelerometer-based system, 98.9% accuracy of elementary pose recognition by the combined accelerometer and video-based system, and 80% accuracy of complex outdoor activity recognition by the accelerometer-based wearable system.

Computerized recognition of human emotions enriches the man–machine interaction with a new personal and behavioral aspect. Firstly, because the influence of emotions on the human performance can be objectively assessed and predicted using standardized stimuli, secondly, because an emotionsensitive computer system can be programmed to react adequately. This paper presents an investigation of emotional influence on the human scanpath. The proposed method assumes that the emotional state of the observer can distract his or her visual attention and can be reliably expressed in parameters of eye movements. We performed visual task experiments in order to record scanpaths from volunteers under auditory stress of controlled intensity. We used a calibrated set of stimuli and controlled the response of volunteers’ central nervous system expressed by the heart rate. For each efficiently stimulated participant, we related the scanpath parameters to the accuracy of solving a given task and to participant’s comment. As a principal result, we obtained a significant change of (1) saccade frequency in 90% and (2) maximum velocity in fixation phase in 80% of participants under stress. These results prove the influence of emotions on visual acuity, feasibility of eyetracking-based assessment of emotional state and motivate further investigations.

Health monitoring and body area network (BAN) applications require wireless intelligent monitoring devices and information systems. The aim of our research is to propose a prototype of wearable wireless monitoring device optimized to supervising the patient and examine the influence of movement on the heart rate during normal daily activities. Main purpose of the proposed system consists in simultaneous acquisition and automatic analysis of two bipolar ECG and three-axes acceleration (ACC) signals measured by means of wireless, battery-operated prototype of ECG module. The processing of the ECG and ACC data is performed by the custom-developed software installed on PC. The system was tested on 10 healthy volunteers.