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"This book provides a far-sighted perspective on the role of wearable and wireless systems for movement disorder evaluation, such as Parkinsons disease and Essential tremor. These observations are brought together in the application of quantified feedback for deep brain stimulation systems using the wireless accelerometer and gyroscope of a smartphone to determine tuning efficacy. The perspective of the book ranges from the pioneering application of these devices, such as the smartphone, for quantifying Parkinsons disease and Essential tremor characteristics, to the current state of the art. Dr. LeMoyne has published multiple first-of-their-kind applications using smartphones to quantify movement disorder, with associated extrapolation to portable media devices."

"The systems biology of parkinson’s disease will be underpinned by new measurement techniques. This is particularly true of the pathology of Parkinson's Disease, where recent developments in brain imaging have offered new insights into the morphology of dopaminergic neurons that have profound implications for the special vulnerability and role of this class of neurons."

"This monograph develops a framework for modeling and solving utility maximization problems in nonconvex wireless systems. The first part develops a model for utility optimization in wireless systems. The model is general enough to encompass a wide array of system configurations and performance objectives. Based on the general model, a set of methods for solving utility maximization problems is developed in the second part of the book. The development is based on a careful examination of the properties that are required for the application of each method. This part focuses on problems whose initial formulation does not allow for a solution by standard methods and discusses alternative approaches. The last part presents two case studies to demonstrate the application of the proposed framework. In both cases, utility maximization in multi-antenna broadcast channels is investigated."

""Organized around the central theme of homeostasis, HUMAN PHYSIOLOGY helps students understand how each component of the course depends on the others and appreciate the integrated functioning of the human body. Author Lauralee Sherwood uses clear straightforward language, analogies, and frequent references to everyday experiences to help students learn and relate to the physiology concepts. The updated art program and new digital resources - including robust 3D animations - enable students to visualize important concepts and processes. By focusing on the core principles and sharing enthusiasm for the subject matter, Sherwood provides a solid foundation for future courses and careers in the health profession."--Pub. desc."

"Penyakit Parkinson atau yang biasa disebut PD merupakan gangguan pada sistem koordinasi gerakan manusia yang ditandai dengan gejala motorik dan non-motorik. Pada stadium lanjut PD, diagnosis klinis cukup jelas dalam pendeteksian. Namun, pada tahap awal, ketika gejala masih belum terlihat dengan jelas, diagnosis menjadi sulit dan terkadang pasien tetap tidak terdiagnosis atau bahkan salah diagnosis. Penelitian ini berfokus pada identifikasi faktor-faktor yang dapat menjadi gejala awal PD berdasarkan gangguan aktivitas keseharian dan gangguan perilaku tidur Rapid Eye Movement. Penelitian ini juga membahas klasifikasi penderita PD stadium awal menggunakan model klasifikasi statistika Classification tree beserta penanganan masalah missing value yang terjadi pada data PD. Faktor penting berdasarkan model Classification Tree adalah tremor, dress difficulty, speech difficulty, skor gangguan perilaku tidur REM, dan usia. Diperoleh model classification tree dengan melakukan proses penanganan missing value menggunakan metode K-Nearest Neighbour. Model tersebut memberikan nilai akurasi sebesar 86.5%, sensitivitas sebesar 80%, spesifisitas sebesar 91.57% dan AUC sebesar 0.858.

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Parkinson’s Disease or commonly known as PD is a disorder in human movement coordinator system that are characterized by motoric and non-motoric symptoms. At the late stage of PD, clinical diagnosis is relatively easy to detect because the symptoms are clear-cut. However, when the symptoms are often incomplete or subtle, in the initial stage, diagnosis becomes difficult and sometimes subject still remain undiagnosed or even misdiagnosed. This research focuses on identifying factors in early stage PD based on patient daily activities and rapid eye movement sleeping behaviour disorder (RBD). Data analysis was conducted using classification tree method, to classify early stage PD patients or healthy control patients. Missing values were handled with k-Nearest Neighbour (kNN) method. The results were satisfactory, with the classification accuracy of 86.5%, sensitivity 80%, specificity 91.57% and AUC 0.858. It is also found that tremor, dressing difficulty, speech difficulty, RBD questionnaire score, and age are important in differentiating early stage PD from the healthy control."