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In this contribution, a first prototype for mobile respiratory motion detection using optical fibers embedded into textiles is presented. The developed system consists of a T-shirt with an integrated fiber sensor and a portable monitoring unit with a wireless communication link enabling the data analysis and visualization on a PC. A great effort is done worldwide to develop mobile solutions for health monitoring of vital signs for patients needing continuous medical care. Wearable, comfortable and smart textiles incorporating sensors are good approaches to solve this problem. In most of the cases, electrical sensors are integrated, showing significant limits such as for the monitoring of anaesthetized patients during Magnetic Resonance Imaging (MRI). OFSETH (Optical Fibre Embedded into technical Textile for Healthcare) uses optical sensor technologies to extend the current capabilities of medical technical textiles.

Deep brain stimulation (DBS) surgery is most effective in reducing the symptoms of Parkinson's disease and essential tremor. At present, there is no designated instrumental method for measuring the immediate effects of DBS. This paper presents the concept of a glove monitoring system for DBS. With the benefits of microelectromechanical systems, inertial measurement unit, and force sensitive resistor (FSR), the system is portable and can be integrated into a textile glove. Tremors, bradykinesia, and rigidity assessments are performed by the system. Several test tasks are chosen to be performed during DBS surgery to evaluate the electrode's position and stimulation intensity. Each quantified symptom severity of the patient is added to a list shown in the graphical user interface for comparison. Comparative experiments between the prototype and an electromagnetic motion tracking system were presented. The FSR boxes were validated with weights. Experimental results show that this system is reliable for tremor amplitude determination, movement angles measurement, and resistance measurement to a passive movement. In addition, it can be found that inconsistent tremor movements have an influence on the tremor amplitude calculation done with power spectral density estimation.Index Terms-MEMS IMU, glove monitoring system, parkinson's disease quantitative assessment, tremor, bradykinesia, rigidity, reliability testing.

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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.