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Mobile Health Technologies

Overview of attention for book
Cover of 'Mobile Health Technologies'

Table of Contents

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    Book Overview
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    Chapter 1 Mobile device for disease diagnosis and data tracking in resource-limited settings.
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    Chapter 2 Microfluidic Devices for Nucleic Acid (NA) Isolation, Isothermal NA Amplification, and Real-Time Detection
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    Chapter 3 Mobile Based Gold Nanoprobe TB Diagnostics for Point-of-Need
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    Chapter 4 Immunofluorescence Microtip Sensor for Point-of-Care Tuberculosis (TB) Diagnosis
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    Chapter 5 Improving Lateral-Flow Immunoassay (LFIA) Diagnostics via Biomarker Enrichment for mHealth.
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    Chapter 6 Microfluidic Toner-Based Analytical Devices: Disposable, Lightweight, and Portable Platforms for Point-of-Care Diagnostics with Colorimetric Detection
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    Chapter 7 Detection of Protein Biomarker Using a Blood Glucose Meter
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    Chapter 8 Microchip ELISA Coupled with Cell Phone to Detect Ovarian Cancer HE4 Biomarker in Urine
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    Chapter 9 Point-of-Care Rare Cell Cancer Diagnostics.
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    Chapter 10 Mobile Flow Cytometer for mHealth.
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    Chapter 11 Mobile Fiber-Optic Sensor for Detection of Oral and Cervical Cancer in the Developing World
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    Chapter 12 Opto-fluidics based microscopy and flow cytometry on a cell phone for blood analysis.
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    Chapter 13 Optofluidic Device for Label-Free Cell Classification from Whole Blood
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    Chapter 14 A Wearable Sensing System for Assessment of Exposures to Environmental Volatile Organic Compounds
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    Chapter 15 Quantitative Point-of-Care (POC) Assays Using Measurements of Time as the Readout: A New Type of Readout for mHealth.
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    Chapter 16 Smartphone-Based Fluorescence Detector for mHealth.
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    Chapter 17 Two-Layer Lab-on-a-Chip (LOC) with Passive Capillary Valves for mHealth Medical Diagnostics.
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    Chapter 18 Spectrometry with Consumer-Quality CMOS Cameras
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    Chapter 19 Mobile Phone Based Electrochemiluminescence Detection in Paper-Based Microfluidic Sensors
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    Chapter 20 iStethoscope: A Demonstration of the Use of Mobile Devices for Auscultation
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    Chapter 21 iPhysioMeter: A Smartphone Photoplethysmograph for Measuring Various Physiological Indices
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    Chapter 22 Smartphone Attachment for Stethoscope Recording
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    Chapter 23 Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor
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    Chapter 24 Measuring tremor with a smartphone.
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    Chapter 25 The Use of Single-Electrode Wireless EEG in Biobehavioral Investigations
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    Chapter 26 Smartphone Based Monitoring System for Long-Term Sleep Assessment
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    Chapter 27 Intracranial Ventricular Catheter Placement with a Smartphone Assisted Instrument
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    Chapter 28 High-Resolution Microendoscope for the Detection of Cervical Neoplasia
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    Chapter 29 Skin Lesions Image Analysis Utilizing Smartphones and Cloud Platforms
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    Chapter 30 Melanoma and other skin lesion detection using smart handheld devices.
Attention for Chapter 23: Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor
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Chapter title
Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor
Chapter number 23
Book title
Mobile Health Technologies
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2172-0_23
Pubmed ID
Book ISBNs
978-1-4939-2171-3, 978-1-4939-2172-0
Authors

Robert LeMoyne, Timothy Mastroianni

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Taiwan 1 <1%
Unknown 101 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 17%
Student > Bachelor 16 16%
Researcher 13 13%
Student > Ph. D. Student 13 13%
Student > Doctoral Student 10 10%
Other 21 20%
Unknown 13 13%
Readers by discipline Count As %
Engineering 16 16%
Medicine and Dentistry 16 16%
Computer Science 13 13%
Nursing and Health Professions 10 10%
Sports and Recreations 6 6%
Other 21 20%
Unknown 21 20%