title: Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment.
abstract: The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units. Several motor tasks were expert-labeled and used for classification. We specifically focused on the detection of bradykinesia. For this, we compared standard machine learning pipelines with deep learning based on convolutional neural networks. Our results showed that deep learning outperformed other state-of-the-art machine learning algorithms by at least 4.6 % in terms of classification rate. We contribute a discussion of the advantages and disadvantages of deep learning for sensor-based movement assessment and conclude that deep learning is a promising method for this field.
authors.forename: Bjoern M
authors.initials: BM
authors.lastname: Eskofier
authors.forename: Sunghoon I
authors.initials: SI
authors.lastname: Lee
authors.forename: Jean-Francois
authors.initials: JF
authors.lastname: Daneault
authors.forename: Fatemeh N
authors.initials: FN
authors.lastname: Golabchi
authors.forename: Gabriela
authors.initials: G
authors.lastname: Ferreira-Carvalho
authors.forename: Gloria
authors.initials: G
authors.lastname: Vergara-Diaz
authors.forename: Stefano
authors.initials: S
authors.lastname: Sapienza
authors.forename: Gianluca
authors.initials: G
authors.lastname: Costante
authors.forename: Jochen
authors.initials: J
authors.lastname: Klucken
authors.forename: Thomas
authors.initials: T
authors.lastname: Kautz
authors.forename: Paolo
authors.initials: P
authors.lastname: Bonato
mesh_terms: D000368:Aged; D005121:Extremities / Q000502:physiology; D005260:Female; D006801:Humans; D018476:Hypokinesia / Q000175:diagnosis / Q000503:physiopathology; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000175:diagnosis / Q000503:physiopathology* / Q000534:rehabilitation; D012720:Severity of Illness Index; D012984:Software