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Monitoring Periodic Limb Movements Using Wearable Accelerometers

This study explores the potential of using off-the-shelf accelerometers to detect periodic limb movements during sleep, a common issue affecting sleep quality and linked to conditions such as sleep apnea, COPD, and hypertension. The researchers tested the feasibility of this approach against gold standard polysomnography, highlighting the benefits of cost-effectiveness and ease of use for long-term patient monitoring post-therapy. The study involved two patients at Clinic Bad Reichenhall using Philips Respironics Alice 5 PSG and Actigraph GT3X accelerometers. Initial results showed promising high sampling rates and contrast with previous findings. Access the software and explore the results at code.google.com/p/movyzer/.

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Monitoring Periodic Limb Movements Using Wearable Accelerometers

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  1. Detecting Periodic Limb Movements with Off-the-shelf AccelerometersAndré Diasa,b,e, Lukas Gorzelniakb,c, JulianeRudnikd, DraganStojanovicd, Alexander Horscha,b,e,faNorwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, NorwaybInstitut für Medizinische Statistik und Epidemiologie, Technische Universität München, GermanycInstitute forEpidemiology II, HelmholtzZentrummünchen, German Research Center for Environmental HealthdClinic Bad Reichenhall, Center for Rehabilitation, Pneumology and Orthopedics, GermanyeComputer Science Department, University of Tromsø, NorwayfDepartment of Clinical Medicine, University of Tromsø, Norway

  2. PeriodicLimbmovements • Afectssleepquality • Related to sleepapnea, COPD, hypertension

  3. Gold Standard polysomnography (PSG): lab, expensive, sleep over

  4. Can we use accelerometers? • Cheap, easy to use • Follow up of patients after therapy • Self assessment

  5. Subjects and materials • Two patients at Clinic Bad Reichenhall • PSG: Philips Respironics Alice 5 • Accelerometer: Actigraph GT3X • 30Hz, 3-axis, pre-filtered • Both legs at ankle

  6. Software • code.google.com/p/movyzer/ • Similarity function (1) GT3X Graph (left leg), (2) GT3X Graph (right leg), (3) PSG Graph, (4) Log field, (5) Parameters

  7. Results

  8. Discussion • 8% similarity: far from relevant for medical applications • Other authors have reported underestimation of accelerometers • But we are in contrast • higher sampling: 100hz

  9. Unpublished results

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