Using mobile phones for activity recognition in Parkinson's patients

scientific article

Using mobile phones for activity recognition in Parkinson's patients is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.3389/FNEUR.2012.00158
P932PMC publication ID3491315
P698PubMed publication ID23162528
P5875ResearchGate publication ID233539714

P50authorKonrad KördingQ18153251
P2093author name stringMark V Albert
Mark Shapiro
Santiago Toledo
P2860cites workAmbulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly.Q52013940
Continuous monitoring and quantification of multiple parameters of daily physical activity in ambulatory Duchenne muscular dystrophy patientsQ62812867
Exercise to improve spinal flexibility and function for people with Parkinson's disease: a randomized, controlled trialQ64868838
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Classification of basic daily movements using a triaxial accelerometerQ80905749
Parkinson's disease: clinical features and diagnosisQ22242021
The effectiveness of exercise interventions for people with Parkinson's disease: A systematic review and meta-analysisQ22252884
Measuring generalization of visuomotor perturbations in wrist movements using mobile phonesQ33918144
Diagnostic criteria for Parkinson diseaseQ34489839
Which measures of physical function and motor impairment best predict quality of life in Parkinson's disease?Q35434976
Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement.Q35767076
Accelerometry: a technique for quantifying movement patterns during walkingQ37051878
The effects of exercise on balance in persons with Parkinson's disease: a systematic review across the disability spectrum.Q37407804
Machine learning methods for classifying human physical activity from on-body accelerometers.Q39947964
Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030.Q40273125
Patient compliance with paper and electronic diariesQ47980863
Rapid tremor frequency assessment with the iPhone accelerometerQ50265781
Single-accelerometer-based daily physical activity classification.Q51769190
Ambulatory monitoring of physical activities in patients with Parkinson's disease.Q51898593
Sparse multinomial logistic regression: fast algorithms and generalization bounds.Q51971885
P921main subjectParkinson's diseaseQ11085
activity recognitionQ4677630
P304page(s)158
P577publication date2012-11-07
P1433published inFrontiers in NeurologyQ15817039
P1476titleUsing mobile phones for activity recognition in Parkinson's patients
P478volume3