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Parkinson's disease (PD) is a degenerative neurological disorder. Patients suffer from different movement disturbances. Amongst others, freezing of gait (FOG) is a common and disabling feature. A new method for FOG detection using a garment with integrated accelerometers, the MiMed-Pants, is presented and evaluated. MiMed-Pants are loose fitting washable pants for measuring movements and were previously developed. The accelerations of shanks and belt of 6 patients were recorded while walking on two standardized courses. The occurrence of FOG were detected and documented both by the new method and by a physician. Those recordings were then compared afterwards to determine the new method's sensitivity and specificity. With this wearable measurement device FOG could be detected without the distracting effects of an extensive measurement installation.

Physical examination, interviews with patients and the results of rating scales for movement disturbances are the basis for the assessment of Parkinson's disease (PD). However, subjectivity in the assessment of the symptoms and the short period of observation are disadvantageous. This paper presents the results of a study to assess the feasibility of using accelerometer data, acquired from smart clothes, to estimate the severity of tremor in patients with PD. Algorithms were implemented to estimate the severity of rest and postural tremor of hands from accelerometer data features. The system developed consists of a pullover with eight integrated accelerometers and a computer. The newly developed system for the detection and assessment of tremor was tested with PD patients. System-based estimates were compared with clinical scores derived via visual inspection of video recordings taken while patients performed a series of standardized motor tasks. A quantifiable objective data acquisition by means of a portable wireless system could evaluate the motor disorders better.

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In this paper, a new garment for automatic fall detection and alert is presented for the first time. It includes a washable pullover with integrated acceleration sensors, evaluation and control electronics. The system measures the accelerations at the torso and on the arms in three directions in space. The fall detection is based on recognizing, by means of the sensors, the posture and abnormal acceleration magnitudes usually associated to a fall. The alarm as well as the movement information is sent via a wireless radio link. A fall will be detected within the pullover's electronics. The fall detection system was tested on ten volunteers. The daily life movements are also stored on a memory card. The latter can be read in on a PC. Thanks to an optimized production process, the system can be affordably reproduced in low volume productions and can be adjusted for any usage. The power supply of the system is realized with rechargeable batteries.

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In this contribution, a new concept for an activity recorder and transceiver (ART) is presented. Among the many purposes ART can be used for, this contribution focuses on the development of personal assistant devices for an aging society. Instead of probing a patient's health only when illness occurs, ART offers the possibility to monitor a person ubiquitous in every day life in order e.g. to detect abnormal changes in behavior, mainly based on the recording of discrete events rather than continuous sensor data streams. ARTs are key elements to develop personal assistant devices that are able to support people especially with cognitive impairments to remain living independent and yet secure their home environments. In this document vital demands on such systems will be defined and systematically analyzed. Furthermore the system architecture and possible applications for ARTs will be presented.

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