Deep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...

This paper presents the enhanced remote control and its role in pervasive healthcare in the home. The device was equipped with health-related measurement modules and a message-processing unit. Preliminary results are presented for monitoring of a pulse, hand tremors, grip forces, and for self­ evaluation procedures. The interaction of the device with the smart environment is presented and discussed.

This chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure...

Face detection is often a first step in quantitative analysis of face images. It is an important research area for visible images and recently also for thermography. Due to technological developments thermal cameras may be embedded into wearable devices to provide remote healthcare. In this paper, we compared three algorithms for face detection in thermal images by testing execution time, accuracy, symmetry ratio and false-positives....