# Next-Generation Neurotechnologies Inspired by Motor Primitive Model for Restoring Human Natural Movement

## TL;DR

This paper explores how the motor primitive model can improve neurotechnologies to restore natural human movement through better modeling of neuromotor control.

## Contribution

The paper introduces the motor primitive model as a novel framework to enhance neurotechnologies by enabling more naturalistic and patient-specific motor restoration.

## Key findings

- The motor primitive model offers a low-dimensional framework to deconstruct and reproduce complex motor tasks.
- Current neurotechnologies lack effective modeling of naturalistic motor control, which the MP model can address.
- MP-inspired paradigms have potential to advance neurotechnologies in kinematic, muscular, and neural domains.

## Abstract

Advances in neuroengineering and artificial intelligence are transforming the landscape of motor rehabilitation, aiming to restore human movement as natural as possible. In recent decades, more advanced interventions are increasingly achievable via hybrid robotic systems, neuroprosthetics, and brain–computer interfaces. However, a fundamental gap of these neurotechnologies remains in modeling the complexity of neuromotor control, particularly how the central nervous system coordinates high-dimensional motor outputs in naturalistic behaviors. Rooted in theoretical neuroscience, the motor primitive (MP) model proposes an adaptable framework to deconstruct and reproduce motor tasks through low-dimensional modules. Interestingly, recent studies have indicated that the MP model may reform current-generation neurotechnologies by digitally shaping the course of human–machine interaction. In this narrative review, we will critically examine conventional target settings and identify their limitations in guiding biomimetic control in neurotechnologies. We then introduce the MP model with its machine learning and physiological scaffolds for better understanding and replicating human natural movement. Finally, we will present its potential in facilitating the next-generation neurotechnologies across kinematic, muscular, and neural domains. By modeling motor control in human and neuroengineering, we believe that the MP-inspired paradigms can initiate a new era of intelligent, patient-specific, and naturalistic motor restoration for various neurological and traumatic diseases.