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Wearable and Wireless Systems for Healthcare II pp 1–15Cite as

Wearable and Wireless Systems for Movement Disorder Evaluation and Deep Brain Stimulation Systems

Part of the Smart Sensors, Measurement and Instrumentation book series (SSMI,volume 31)

Abstract

The implementation of wearable and wireless systems for deep brain stimulation offers the opportunity to substantially advance the treatment of progressive neurodegenerative movement disorders, such as Parkinson’s disease and Essential tremor. Deep brain stimulation offers an efficacious alternative regarding scenarios for which the intervention by medication has become intractable while avoiding the permanency of ablative neurosurgery. Even subsequent to the expert surgical application of the deep brain stimulation system, the acquisition of the optimal parameter configuration is inherently resource intensive and challenging in nature. With the advent of wearable and wireless systems, the response to therapy intervention for movement disorder status can be objectively quantified through the inertial sensor signal, such as an accelerometer and gyroscope. Furthermore, wireless connectivity to the Internet enables experimental and post-processing resources to be remotely situated effectively anywhere in the world. With machine learning amended to the post-processing capability, clinical diagnostic acuity is substantially advanced. Foundational subjects are elucidated, such a general perspective regarding Parkinson’s disease and Essential tremor, traditional ordinal methodologies for diagnosing severity, and the development of deep brain stimulation including surgical techniques for installation. The role of wearable and wireless systems, such as the smartphone, for quantifying the status of neurodegenerative movement disorders, such as Parkinson’s disease and Essential tremor, is presented. The utility of applying machine learning for augmenting diagnostic acuity of movement disorder status is addressed. The integration of wearable and wireless systems, such as the smartphone, with machine learning is discussed for the ability to distinctively classify between deep brain stimulation set to “On” and “Off” status for Parkinson’s disease and Essential tremor. The amalgamation of wearable and wireless systems with deep brain stimulation using machine learning as an augmented post-processing application implicate the evolutionary trends for the ability to achieve closed-loop optimization of parameter configurations with the development of Network Centric Therapy for a quantum leap in the treatment intervention for neurodegenerative movement disorders, such as Parkinson’s disease and Essential tremor.

Keywords

  • Wearable and wireless system
  • Smartphone
  • Wireless inertial sensor
  • Accelerometer
  • Gyroscope
  • Deep brain stimulation system
  • Movement disorders
  • Parkinson’s disease
  • Essential tremor
  • Parameter configuration
  • Optimization
  • Closed-loop tuning
  • Network Centric Therapy

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Authors and Affiliations

  1. Department of Biological Sciences and Center for Bioengineering Innovation, Northern Arizona University, Flagstaff, AZ, USA

    Robert LeMoyne

  2. Independent, Pittsburgh, PA, USA

    Timothy Mastroianni

  3. Department of Neurosurgery Allegheny General Hospital, Allegheny Health Network Neuroscience Institute, Pittsburgh, PA, USA

    Donald Whiting & Nestor Tomycz

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LeMoyne, R., Mastroianni, T., Whiting, D., Tomycz, N. (2019). Wearable and Wireless Systems for Movement Disorder Evaluation and Deep Brain Stimulation Systems. In: Wearable and Wireless Systems for Healthcare II. Smart Sensors, Measurement and Instrumentation, vol 31. Springer, Singapore. https://doi.org/10.1007/978-981-13-5808-1_1

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