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hmu

asmeragliuolo@gmail.com

another paper:

Using data from the Microsoft Kinect 2 to determine postural stability in healthy subjects: A feasibility trial
or
machine learning is how a Kinect can tell what you are doing better than a fancy force plate can
by Behdad Dehbandi, Alexandre Barachant, Anna Smeragliuolo, John Davis Long, Silverio Joseph Bumanlag, Victor He, Anna Lampe, and David Putrino

read it here
Fig 1. Experimental layout for data collection: subjects sat on a rectangular box that was placed in the center of the KFP at a distance of 2.7 meters from the MK2. The MK2 was mounted on a tripod 0.92 meters from the floor. Fig 2. Three postural conditions. a) Both feet on the ground. b) One foot off the ground. c) Both feet off the ground. Fig 6. t-SNE representation of the dataset for the MK2 (left) and the KFP (right). A clear separation between tasks can be observed for both devices, but the MK2 data are more separable. Each cluster is formed by the points of the 3 conditions performed under the corresponding task. A zoom over the cluster of task 5 highlights a lower separation of the conditions.