No abstract

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.

No abstract