A special purpose embedded system for neural machine interface for artificial legs

Abstract

This paper presents a design and implementation of a neural-machine interface (NMI) for artificial legs that can decode amputee's intended movement in real time. The newly designed NMI integrates an FPGA chip for fast processing and a microcontroller unit (MCU) with multiple on-chip analog-to-digital converters (ADCs) for real-time data sampling. The resulting embedded system is able to sample in real time 12 EMG signals and 6 mechanical signals and execute a special complex phase-dependent classifier for accurate recognition of the user's intended locomotion modes. The implementation and evaluation are based on Altera's Stratix III 3S150 FPGA device coupled with Freescale's MPC5566 MCU. The experimental results for classifying three locomotion modes (level-ground walking, stairs ascent, and stairs descent) based on data collected from an able-bodied human subject have shown acceptable performance for real-time controlling of artificial legs.

Fig. 1

System architecture of designed NMI for artificial legs.

Fig. 2

Architecture of neuromuscular-mechanical fusion-based PR algorithm for artificial legs.

Fig. 3

The prototype board based on MPC5566 EVB and DE3 education board.

Fig. 4

Timing control and memory management of real-time control algorithm for one channel.

Fig. 5

Task stages and data flows of phase-dependent PR.