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Hyperdimensionnal computing for biosignal-based gesture recognition

Technological challenge: New computing paradigms, circuits and technologies, incl. quantum (learn more)

Department: Département Composants Silicium (LETI)

Laboratory: Laboratoire de Composants Mémoires

Start Date: 01-10-2022

Location: Grenoble

CEA Code: SL-DRT-22-0482

Contact: sylvain.barraud@cea.fr

In this work, we propose to study a new paradigm of computation, which is called ?hyperdimensional computing? (HDC). During the last years, brain-inspired hyperdimensional computing, based on the use of hypervectors, has demonstrated promising results in various domains including language classification, brain computer interfaces, DNA pattern matching, etc. Very robust and noise-tolerant, hyperdimensional computing is now implemented with non-volatiles memories in order to significantly reduce the energy consumption by limiting the data transfer between the memory and CPU. During this thesis, we propose to evaluate the robustness of this model for the recognition and classification of biological signals (electromyography, electroencephalography) with the objective of developing healthcare intelligence artificial solutions.

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