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Recent studies suggest that the quality of recovery after a stroke can be increased by early and more intensive rehabilitation. Portable unobtrusive devices are promising candidates for the realization of stroke-rehabilitation systems that complement care in the post-acute rehabilitation phase, both in the clinic and at home. The proposed system allows patients to increase the amount of motor exercise they can perform in autonomy, providing them with a real-time feedback based on wearable sensors embedded in the garment's tissue across the upper limb and trunk. A dynamic time warping algorithm allows for the recognition of correct and incorrect motor exercises. After the feedback phase, data are stored in a central location for review and statistics. Workstations can be installed either at home or at the hospital to support patients, independent of their location. The performance of the system on healthy subjects was quantified for seven types of motor exercises for upper limb's rehabilitation. Finally, we present the preliminary results of a pilot clinical study to test the system's acceptability and usability by post-stroke patients, and physicians in a clinical setting.

Stroke is a serious neurological accident which accounts for a wide fraction of the healthcare costs in industrialized societies. Recovery from stroke and other neurological accidents usually include motor rehabilitation, maintained for several months, and logopedic training for the recovery of cognitive and speech abilities. The MyHeart consortium is addressing several aspects of cardiovascular diseases' management by combining clothes with embedded biomedical sensors and information technologies. One of the application areas is especially devoted to supporting Neurological Rehabilitation (NR). This article describes how MyHeart's Concept NR is structured and how technologies are leveraged to support both motor rehabilitation and speech/cognitive training. Information technology and garment-embedded sensors, combined, permit assisted training both at the clinic and at home, after discharge from the intensive care unit.

The recent integration of telephony systems with information and communication technology (ICT) enables the development of innovative tools for telemedicine. The dissemination and widespread acceptance of telephone-based care monitoring systems challenge the researcher to deal with the cognitive factors involved in the patient-physician interaction, and the way they should be to shape up the technological solutions. This paper proposes a model that describes the impact of socio-cognitive factors in the complex process of health care management. The model has been used to design and develop a telephone system for the management of hypertensive patient within the EU funded Homey project. The knowledge existed in a widely accepted guideline for the care of hypertension has been represented and augmented through the proposed cognitive model. The final product is an intelligent system able to manage an adaptive dialogue. It monitors patients' adherence and increases their involvement by promoting self-care through frequent virtual visits, which is complementary to the traditional face-to-face encounters with their primary care physicians.

Stroke is a serious neurological accident which accounts for a wide fraction of the healthcare costs in industrialized societies. Recovery from stroke and other neurological accidents usually include motor rehabilitation, maintained for several months, and logopedic training for the recovery of cognitive and speech abilities. The MyHeart consortium is addressing several aspects of cardiovascular diseases' management by combining clothes with embedded biomedical sensors and information technologies. One of the application areas is especially devoted to supporting Neurological Rehabilitation (NR). This article describes how MyHeart's Concept NR is structured and how technologies are leveraged to support both motor rehabilitation and speech/cognitive training. Information technology and garment-embedded sensors, combined, permit assisted training both at the clinic and at home, after discharge from the intensive care unit. [ABSTRACT FROM AUTHOR]

Summary: Recent advances in automatic speech recognition and related technologies allow computers to carry on conversations by telephone. We developed an intelligent dialogue system that interacts with hypertensive patients to collect data about their health status. Patients thus avoid the inconvenience of traveling for frequent face to face visits to monitor the clinical variables they can easily measure at home; the physician is facilitated in acquiring patient information and cardiovascular risk, which is evaluated from the data according to noted guidelines. Controlled trials to assess the clinical efficacy are under way. [Copyright &y& Elsevier]