The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to cloud computing resources.Imperative to the realization of these objectives the organization of the software development process. Requirements and pseudo code are derived and software automation using Python for post-processing the inertial signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provides. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.

Book Information
ISBN 9789811235955
Author Robert Lemoyne
Format Hardback
Page Count 250
Imprint World Scientific Publishing Co Pte Ltd
Publisher World Scientific Publishing Co Pte Ltd