Need help?
For technical questions about your Moticon products
Want to say hello?
Drop us a message for general questions or inquiries
Want a live demo?
See our products live and ask your questions
Interested in prices?
Get an individual quote with the items you need
Always just a call away
+49 89 2000 301 60


| 2021

The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients

Gait analysis is crucial for the detection and management of various neurological and musculoskeletal disorders. The identification of gait events is valuable for enhancing gait analysis, developing accurate monitoring systems, and evaluating treatments for pathological gait. The aim of this work is to introduce the Smart-Insole Dataset to be used for the development and evaluation of computational methods focusing on gait analysis. Towards this objective, temporal and spatial characteristics of gait have been estimated as the first insight of pathology. The Smart-Insole dataset includes data derived from pressure sensor insoles, while 29 participants (healthy adults, elderly, Parkinson’s disease patients) performed two different sets of tests: The Walk Straight and Turn test, and a modified version of the Timed Up and Go test. A neurologist specialized in movement disorders evaluated the performance of the participants by rating four items of the MDS-Unified Parkinson’s Disease Rating Scale. The annotation of the dataset was performed by a team of experienced computer scientists, manually and using a gait event detection algorithm. The results evidence the discrimination between the different groups, and the verification of established assumptions regarding gait characteristics of the elderly and patients suffering from Parkinson’s disease.


gait analysis, parkinson’s disease, insoles, pressure sensors, dataset


Chariklia Chatzaki, Vasileios Skaramagkas, Nikolaos Tachos, Georgios Christodoulakis, Evangelia Maniadi, Zinovia Kefalopoulou, Dimitrios I. Fotiadis, Manolis Tsiknakis

Institution / Department

Biomedical Informatics and eHealth Laboratory, Department of Electrical and Computer Engineering, Hellenic Mediterranean University

The form was sent successfully.

You will be contacted shortly.


Stay one step ahead!

Subscribe to our newsletter for the latest information on case studies, webinars, product updates and company news

Get support

Check our FAQ database for answers to frequently asked questions!

Describe your issue in as much detail as possible. Include screenshots or files if applicable.

Have a general inquiry?

Write us a message for general questions about products and solutions or if you’d like to discuss other topics.