Smart Sensor Systems: Emerging Technologies and Applications

Chapter 8Exploring Smart Sensors for Neural Interfacing

Tim Denison, Peng Cong and Pedram Afshar

Medtronic Neuromodulation, Minneapolis, USA

Elements of this work where published in reference [1]. The authors wish to thank Dr. Brian Litt at UPenn for helpful conversations on this subject.

8.1 Introduction

Neuromodulation aims to improve disease-state control with ongoing therapy adjustments that enhance therapeutic response while minimizing clinician and patient burden. Innovation in neuromodulation might be facilitated by modeling the interaction between device and the nervous system in a dynamic control framework. While advances in sensing [1], [2], therapy delivery [3], [4], and understanding the pathophysiology of disease states [5–7] have already aimed to improve device performance, dynamic control theory provides an alternative paradigm to advance the field of neuromodulation. As illustrated in Figure 8.1, a classic control paradigm consists of a “plant” (the nervous system), an actuator (neural stimulator), a sensor (clinical data collector), and a state estimator (assessment by the clinician, patient, caregiver or an automated algorithm). In this context, the actuator is any device or method that modulates the activity of a functional group of neurons. We call these “stimulators” for simplicity. Within a dynamic control framework, the detailed, desired function for each subcomponent is:

• Defining the patient's desired “state” using objective (preferably quantitative) ...