Matching Items (5)
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Description
Advances in miniaturized sensors and wireless technologies have enabled mobile health systems for efficient healthcare. A mobile health system assists the physician to monitor the patient's progress remotely and provide quick feedbacks and suggestions in case of emergencies, which reduces the cost of healthcare without the expense of hospitalization. This

Advances in miniaturized sensors and wireless technologies have enabled mobile health systems for efficient healthcare. A mobile health system assists the physician to monitor the patient's progress remotely and provide quick feedbacks and suggestions in case of emergencies, which reduces the cost of healthcare without the expense of hospitalization. This work involves development of an innovative mobile health system with adaptive biofeedback mechanism and demonstrates the importance of biofeedback in accurate measurements of physiological parameters to facilitate the diagnosis in mobile health systems. Resting Metabolic Rate (RMR) assessment, a key aspect in the treatment of diet related health problems is considered as a model to demonstrate the importance of adaptive biofeedback in mobile health. A breathing biofeedback mechanism has been implemented with digital signal processing techniques for real-time visual and musical guidance to accurately measure the RMR. The effects of adaptive biofeedback with musical and visual guidance were assessed on 22 healthy subjects (12 men, 10 women). Eight RMR measurements were taken for each subject on different days under same conditions. It was observed the subjects unconsciously followed breathing biofeedback, yielding consistent and accurate measurements for the diagnosis. The coefficient of variation of the measured metabolic parameters decreased significantly (p < 0.05) for 20 subjects out of 22 subjects.
ContributorsKrishnan, Ranganath (Author) / Tao, Nongjian (Thesis advisor) / Forzani, Erica (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Title: A Mobile Health Application for Tracking Patients' Health Record Abstract Background: Mobile Health (mHealth) has recently been adopted and used in rural communities in developing countries to improve the quality of healthcare in those areas. Some organizations use mHealth application to track pregnancy and provide routine checkups for pregnant

Title: A Mobile Health Application for Tracking Patients' Health Record Abstract Background: Mobile Health (mHealth) has recently been adopted and used in rural communities in developing countries to improve the quality of healthcare in those areas. Some organizations use mHealth application to track pregnancy and provide routine checkups for pregnant women. Other organizations use mHelath application to provide treatment and counseling services to HIV/AIDs patients, and others are using it to provide treatment and other health care services to the general populations in rural communities. One organization that is using mobile health to bring primary care for the first time in some of the rural communities of Liberia is Last Mile Health. Since 2015, the organization has trained community health assistants (CHAs) to use a mobile health platform called Data Collection Tools (DCTs). The CHAs use the DCT to collect health data, diagnose and treat patients, provide counseling and educational services to their communities, and for referring patients for further care. While it is true that the DCT has many great features, it currently has many limitations such as data storage, data processing, and many others. Objectives: The goals of this study was to 1. Explore some of the mobile health initiatives in developing countries and outline some of the important features of those initiatives. 2. Design a mobile health application (a new version of the Last Mile Health's DCT) that incorporates some of those features that were outlined in objective 1. Method: A comprehensive literature search in PubMed and Arizona State University (ASU) Library databases was conducted to retrieve publications between 2014 and 2017 that contained phrases like "mHealth design", "mHealth implementation" or "mHealth validation". For a publication to refer to mHealth, the publication had to contain the term "mHealth," or contains both the term "health" and one of the following terms: mobile phone, cellular phone, mobile device, text message device, mobile technology, mobile telemedicine, mobile monitoring device, interactive voice response device, or disease management device. Results: The search yielded a total of 1407 publications. Of those, 11 publications met the inclusion criteria and were therefore included in the study. All of the features described in the selected articles were important to the Last Mile Health, but due to issues such as internet accessibility and cellular coverage, only five of those features were selected to be incorporated in the new version of the Last Mile's mobile health system. Using a software called Configure.it, the new version of the Last Mile's mobile health system was built. This new system incorporated features such as user logs, QR code, reminder, simple API, and other features that were identified in the study. The new system also helps to address problems such as data storage and processing that are currently faced by the Last Mile Health organization.
ContributorsKarway, George K. (Author) / Scotch, Matthew (Thesis director) / Kaufman, David (Committee member) / Biomedical Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Mobile health or "mHealth" defines a broad spectrum of medical or public health practice supported by mobile devices. The patient's perception of mobile health applications is the key point in confronting whether or not patients will utilize the tools at their disposal As such, the primary aim of this study

Mobile health or "mHealth" defines a broad spectrum of medical or public health practice supported by mobile devices. The patient's perception of mobile health applications is the key point in confronting whether or not patients will utilize the tools at their disposal As such, the primary aim of this study was to examine participant feedback through quantitative and qualitative measures using the Therapy Evaluation Questionnaire and a patient interview, respectively, to further understand the patient rated acceptability of using BeWell24 and SleepWell24 for improving health outcomes. For BeWell24, it was hypothesized that patients who received the Multicomponent version would report higher acceptability scores than those randomized to the Health Education version. Furthermore, in regard to SleepWell24, it was hypothesized that the SleepWell24 patient would provide positive feedback and suggestions regarding their own experience with the SleepWell24 app. Data from this thesis was pulled from two ongoing randomized controlled trials currently being conducted at the Phoenix Veteran Affairs Health Care Service (PVACHS) and Mayo Clinic hospitals. Means, standard deviations, frequencies, and percentages were commuted to summarize demographics and TEQ scores. In addition, key concepts from a qualitative interview with a SleepWell24 participant were derived. The results showed a greater acceptability of the multicomponent versions of BeWell24 and SleepWell24 but a lower TEQ score of perceived usability. mHealth implementations pose a potential to become an important part of the health sector for establishing innovative approaches to delivering care, and while benefits have been highly praised, it is clear that the perceptions of mHealth must be positive if the technology is to transcend into a practical clinical setting.
ContributorsJimenez, Asael (Author) / Buman, Matthew (Thesis director) / Epstein, Dana (Committee member) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Monitoring vital physiological signals, such as heart rate, blood pressure and breathing pattern, are basic requirements in the diagnosis and management of various diseases. Traditionally, these signals are measured only in hospital and clinical settings. An important recent trend is the development of portable devices for tracking these physiological signals

Monitoring vital physiological signals, such as heart rate, blood pressure and breathing pattern, are basic requirements in the diagnosis and management of various diseases. Traditionally, these signals are measured only in hospital and clinical settings. An important recent trend is the development of portable devices for tracking these physiological signals non-invasively by using optical methods. These portable devices, when combined with cell phones, tablets or other mobile devices, provide a new opportunity for everyone to monitor one’s vital signs out of clinic.

This thesis work develops camera-based systems and algorithms to monitor several physiological waveforms and parameters, without having to bring the sensors in contact with a subject. Based on skin color change, photoplethysmogram (PPG) waveform is recorded, from which heart rate and pulse transit time are obtained. Using a dual-wavelength illumination and triggered camera control system, blood oxygen saturation level is captured. By monitoring shoulder movement using differential imaging processing method, respiratory information is acquired, including breathing rate and breathing volume. Ballistocardiogram (BCG) is obtained based on facial feature detection and motion tracking. Blood pressure is further calculated from simultaneously recorded PPG and BCG, based on the time difference between these two waveforms.

The developed methods have been validated by comparisons against reference devices and through pilot studies. All of the aforementioned measurements are conducted without any physical contact between sensors and subjects. The work presented herein provides alternative solutions to track one’s health and wellness under normal living condition.
ContributorsShao, Dangdang (Author) / Tao, Nongjian (Thesis advisor) / Li, Baoxin (Committee member) / Hekler, Eric (Committee member) / Karam, Lina (Committee member) / Arizona State University (Publisher)
Created2016
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Description
A study was undertaken to examine and test the effectiveness of a self-experimentation model, guided by a mobile app called PACO, in helping college students improve behaviors associated with sleep. Thirteen participants were enrolled in this study and their nightly sleep quality and sleep duration were measured via PACO as

A study was undertaken to examine and test the effectiveness of a self-experimentation model, guided by a mobile app called PACO, in helping college students improve behaviors associated with sleep. Thirteen participants were enrolled in this study and their nightly sleep quality and sleep duration were measured via PACO as they underwent three conditions: a baseline non-intervention phase, an expert-developed intervention phase, in which pre-made intervention examples were provided and used in PACO, and a self-experimentation phase, during which users were invited to develop their own sleep-behavior interventions using PACO. The participants were randomly placed into three groups, and the points of transition between phases was staggered across five weeks according to a multiple baseline design. The goal and hypothesis was to determine if sleep duration and sleep quality (sleep satisfaction) were improved in the final self-experimentation phase compared to the expert-developed experimentation phase and baseline phase, as well as in the expert-developed experimentation phase compared to the baseline phase. The results show little change, and nearly no improvement in the outcome measures between phases, leaving us unable to support the hypothesis. However, the existence of several limitations considered in retrospect, such as the small sample size, the short study time period, and technical difficulties with the PACO application means that no concrete conclusions should be made regarding the effectiveness of the self-experimentation model, nor the usability of PACO. Additional research should be made toward user motivation and modes of teaching the underlying behavioral science principles to casual users to increase effectiveness.
ContributorsNazareno, Alexandra Nicole (Author) / Hekler, Eric (Thesis director) / Walker, Erin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05