title: Ambulatory monitoring of physical activities in patients with Parkinson's disease.
abstract: A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.
authors: Laboratory of Movement Analysis and Measurement (LMAM), Ecole Polytechnique Fédérale de Lausanne (EPFL), STI-LMAM, ELG 239, Lausanne Vaud 1024, Switzerland. arash.salarian@ieee.org
authors: Arash
authors: A
authors: Salarian
authors: Heike
authors: H
authors: Russmann
authors: François J G
authors: FJ
authors: Vingerhoets
authors: Pierre R
authors: PR
authors: Burkhard
authors: Kamiar
authors: K
authors: Aminian
mesh_terms: D000054:Acceleration; D000203:Activities of Daily Living; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004599:Electric Stimulation Therapy; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D009043:Motor Activity; D010300:Parkinson Disease / Q000175:diagnosis* / Q000503:physiopathology* / Q000534:rehabilitation; D016896:Treatment Outcome