Intuitive sequence matching algorithm applied to a sip-and-puff control interface for robotic assistive devices
Fr\'ed\'eric Schweitzer, Alexandre Campeau-Lecours

TL;DR
This paper introduces a sequence matching control algorithm for sip-and-puff interfaces, improving speed and comfort in controlling assistive robotic devices, validated through preliminary tests with healthy subjects.
Contribution
It adapts sequence matching for sip-and-puff control, demonstrating enhanced performance over traditional methods in assistive device interfaces.
Findings
Sequence matching improves control speed and comfort.
Preliminary validation with 8 healthy subjects shows positive results.
Framework paves the way for more advanced algorithms and sensors.
Abstract
This paper presents the development and preliminary validation of a control interface based on a sequence matching algorithm. An important challenge in the field of assistive technology is for users to control high dimensionality devices (e.g., assistive robot with several degrees of freedom, or computer) with low dimensionality control interfaces (e.g., a few switches). Sequence matching consists in the recognition of a pattern obtained from a sensor's signal compared to a predefined pattern library. The objective is to allow the user to input several different commands with a low dimensionality interface (e.g., Morse code allowing inputting several letters with a single switch). In this paper, the algorithm is used in the context of the control of an assistive robotic arm and has been adapted to a sip-and-puff interface where short and long bursts can be detected. Compared to a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGaze Tracking and Assistive Technology · EEG and Brain-Computer Interfaces · Context-Aware Activity Recognition Systems
