Evaluation of Arm Swing Features and Asymmetry during Gait in Parkinson’s Disease Using the Azure Kinect Sensor
Claudia Ferraris,
Gianluca Amprimo,
Giulia Masi,
Luca Vismara,
Riccardo Cremascoli,
Serena Sinagra,
Giuseppe Pettiti,
Alessandro Mauro,
Lorenzo Priano
Affiliations
Claudia Ferraris
Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Gianluca Amprimo
Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Giulia Masi
Department of Neurosciences, University of Turin, Via Cherasco 15, 10100 Torino, Italy
Luca Vismara
Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neurorehabilitation, S. Giuseppe Hospital, Strada Luigi Cadorna 90, 28824 Piancavallo, Italy
Riccardo Cremascoli
Department of Neurosciences, University of Turin, Via Cherasco 15, 10100 Torino, Italy
Serena Sinagra
Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neurorehabilitation, S. Giuseppe Hospital, Strada Luigi Cadorna 90, 28824 Piancavallo, Italy
Giuseppe Pettiti
Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Alessandro Mauro
Department of Neurosciences, University of Turin, Via Cherasco 15, 10100 Torino, Italy
Lorenzo Priano
Department of Neurosciences, University of Turin, Via Cherasco 15, 10100 Torino, Italy
Arm swinging is a typical feature of human walking: Continuous and rhythmic movement of the upper limbs is important to ensure postural stability and walking efficiency. However, several factors can interfere with arm swings, making walking more risky and unstable: These include aging, neurological diseases, hemiplegia, and other comorbidities that affect motor control and coordination. Objective assessment of arm swings during walking could play a role in preventing adverse consequences, allowing appropriate treatments and rehabilitation protocols to be activated for recovery and improvement. This paper presents a system for gait analysis based on Microsoft Azure Kinect DK sensor and its body-tracking algorithm: It allows noninvasive full-body tracking, thus enabling simultaneous analysis of different aspects of walking, including arm swing characteristics. Sixteen subjects with Parkinson’s disease and 13 healthy controls were recruited with the aim of evaluating differences in arm swing features and correlating them with traditional gait parameters. Preliminary results show significant differences between the two groups and a strong correlation between the parameters. The study thus highlights the ability of the proposed system to quantify arm swing features, thus offering a simple tool to provide a more comprehensive gait assessment.
