Sensorized garments developed for remote postural and motor rehabilitation

Every day, all around the world, millions of people request postural and/or motor rehabilitation. The rehabilitation process, also known as Tertiary Prevention, intends to be a sort of therapy to restore functionality and self-sufficiency of the patient, and regards not only millions of patients daily, but involves also a huge number of professionals in medical staffs, i.e. specialists, nurses, physiotherapists and therapists, social workers, psychologists, physiatrists. The care is given in hospitals, clinics, geriatric facilities, and with territorial home care. For the large number of patients as well as the medical staff and facilities necessary to support the appropriate postural and motor training, the monetary costs of rehabilitation is so large, it is difficult to estimate. So, every effort towards a simplification of the rehabilitation route is desirable and welcome, and this chapter covers this aspect

On the Performance of Li’s Unsupervised Image Classifier and the Optimal Cropping Position of Images for Forensic Investigations

Images from digital imaging devices are prevalent in society. The signatures of these images can be extracted as sensor pattern noise (SPN) and classified according to their source devices. In this paper, the authors assess the reliability of an unsupervised classifier for forensic investigation of digital images recovered from storage devices and to identify the best position for cropping the images before processing. Cross validation was performed on the classifier to assess the error rate and determine the effect of the size of the sample space and the classifier trainer on the performance of the classifier. Moreover, the authors find that the effect of saturation and subsequently the contamination of the SPN in the images affected performance negatively. To alleviate the negative performance, the authors identify the areas of images where less contamination occurs to perform cropping.</p