High Dimensional Computing Gesture Recognition

The primary objective of this study is the Improvement of gesture recognition and classification accuracy through the use of the HDC algorithm compared to other classification methods (KNN, RF, SGD, NC). The recognition rate will be expressed by the sensitivity and specificity of gesture recognition. The model will be trained on a portion of the dataset and tested on the remaining part to avoid any bias. The secondaries objectives are the : * Improvement of gesture recognition accuracy with our HDC algorithm compared to other standard models. * Calculation of gesture recognition rates depending on the number of electrodes used and their position. * Subject's assessment of device comfort rated above 6 on a 10-level visual analog scale. * Subject's assessment of ease of performing the gesture rated above 6 on a 10-level visual analog scale.

NCT Number	NCT07155460
Lead Sponsor	University Hospital, Grenoble Collaborators: Commissariat à l'Energie Atomique (CEA) Grenoble, CLINATEC
Conditions	Healthy Volunteers
Enrollment	10 participants
Start Date	2026-01-15
Primary Completion	2026-04 (estimated)
Study Completion	2026-06 (estimated)
Updated on ClinicalTrials.gov	2026-01-20