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Mobile Health Technologies

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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
  27. Altmetric Badge
    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
  29. Altmetric Badge
    Chapter 28 High-Resolution Microendoscope for the Detection of Cervical Neoplasia
  30. Altmetric Badge
    Chapter 29 Skin Lesions Image Analysis Utilizing Smartphones and Cloud Platforms
  31. Altmetric Badge
    Chapter 30 Melanoma and other skin lesion detection using smart handheld devices.
Attention for Chapter 16: Smartphone-Based Fluorescence Detector for mHealth.
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Chapter title
Smartphone-Based Fluorescence Detector for mHealth.
Chapter number 16
Book title
Mobile Health Technologies
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2172-0_16
Pubmed ID
Book ISBNs
978-1-4939-2171-3, 978-1-4939-2172-0
Authors

Joshua Balsam, Hugh Alan Bruck, Avraham Rasooly

Abstract

We describe here a compact smartphone-based fluorescence detector for mHealth. A key element to achieving high sensitivity using low sensitivity phone cameras is a capillary array, which increases sensitivity by 100×. The capillary array was combined with a white LED illumination system to enable wide spectra fluorescent excitation in the range of 450-740 nm. The detector utilizes an orthographic projection system to form parallel light projection images from the capillaries at a close distance via an object-space telecentric lens configuration that reduces the total lens-to-object distance while maintaining uniformity in measurement between capillaries. To further increase the limit of detection (LOD), a computational image processing approach was employed to decrease the level of noise. This enables an additional 5-10× decrease in LOD. This smartphone-based detector was used to measure serial dilutions of fluorescein with a LOD of 1 nM with image stacking and 10 nM without image stacking, similar to the LOD obtained with a commercial plate reader. Moreover, the capillary array required a sample volume of less than 10 μl, which is an order of magnitude less than the 100 μl required for the plate reader.As fluorescence detection is widely used in sensitive biomedical assays, the approach described here has the potential to increase mHealth clinical utility, especially for telemedicine and for resource-poor settings in global health applications.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 26%
Student > Doctoral Student 4 15%
Student > Bachelor 3 11%
Student > Postgraduate 3 11%
Researcher 3 11%
Other 4 15%
Unknown 3 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 19%
Psychology 4 15%
Nursing and Health Professions 3 11%
Medicine and Dentistry 3 11%
Engineering 2 7%
Other 6 22%
Unknown 4 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 January 2015.
All research outputs
#20,251,805
of 22,780,967 outputs
Outputs from Methods in molecular biology
#9,885
of 13,094 outputs
Outputs of similar age
#295,679
of 352,963 outputs
Outputs of similar age from Methods in molecular biology
#635
of 996 outputs
Altmetric has tracked 22,780,967 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,094 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 996 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.