Motivational and Intervention Systems and Monitoring with mHealth Tools

Use of mobile and telecommunication technologies has become widespread in the last decade. With this development, use of mobile devices in healthcare (mHealth) is also increasing. Mobile phones, smartphones, and other mobile devices are affordable tools for different health-related services. In my research, with my research team, I have helped to develop several mHealth tools to address the quality of life of cancer survivors, cancer patients, and individuals at increased risk for cancer. Tobacco smoking is the major cause of several types of often-fatal cancers and cardio-respiratory diseases. Optimally, we hypothesize that the most effective mHealth tools should be customized and personalized. For smokers, the goal is to encourage cessation. For cancer survivors, one goal is to increase physical activity, which is associated with decreased rates of recurrent disease. In patients with incurable cancers, efficient and current monitoring of symptoms should contribute to better palliation. This dissertation explores multiple issues in use of mHealth tools with these medical populations. We discuss a general framework for collecting and managing healthcare data and mathematical models for data analysis. The specific contributions of this dissertation are: 1.) The design and development of a culturally tailored customized text messaging system for motivation and intervention; 2.) The design and development of a data collection system for an mHealth intervention, and; 3.) A model for monitoring pain levels using mobile devices

Pain Level Detection From Facial Image Captured by Smartphone

Accurate symptom of cancer patient in regular basis is highly concern to the medical service provider for clinical decision making such as adjustment of medication. Since patients have limitations to provide self-reported symptoms, we have investigated how mobile phone application can play the vital role to help the patients in this case. We have used facial images captured by smart phone to detect pain level accurately. In this pain detection process, existing algorithms and infrastructure are used for cancer patients to make cost low and user-friendly. The pain management solution is the first mobile-based study as far as we found today. The proposed algorithm has been used to classify faces, which is represented as a weighted combination of Eigenfaces. Here, angular distance, and support vector machines (SVMs) are used for the classification system. In this study, longitudinal data was collected for six months in Bangladesh. Again, cross-sectional pain images were collected from three different countries: Bangladesh, Nepal and the United States. In this study, we found that personalized model for pain assessment performs better for automatic pain assessment. We also got that the training set should contain varying levels of pain in each group: low, medium and high

A Novel Real-Time Non-invasive Hemoglobin Level Detection Using Video Images from Smartphone Camera

Hemoglobin level detection is necessary for evaluating health condition in the human. In the laboratory setting, it is detected by shining light through a small volume of blood and using a colorimetric electronic particle counting algorithm. This invasive process requires time, blood specimens, laboratory equipment, and facilities. There are also many studies on non-invasive hemoglobin level detection. Existing solutions are expensive and require buying additional devices. In this paper, we present a smartphone-based non-invasive hemoglobin detection method. It uses the video images collected from the fingertip of a person. We hypothesized that there is a significant relation between the fingertip mini-video images and the hemoglobin level by laboratory gold standard. We also discussed other non-invasive methods and compared with our model. Finally, we described our findings and discussed future works

Toward an mHealth Intervention for Smoking Cessation

The prevalence of tobacco dependence in the United States (US) remains alarming. Invariably, smoke-related health problems are the leading preventable causes of death in the US. Research has shown that a culturally tailored cessation counseling program can help reduce smoking and other tobacco usage. In this paper, we present a mobile health (mHealth) solution that leverages the Short Message Service (SMS) or text messaging feature of mobile devices to motivate behavior change among tobacco users. Our approach implements the Theory of Planned Behavior (TPB) and a phase-based framework. We make contributions to improving previous mHealth intervention approaches by delivering personalized and evidence-based motivational SMS messages to participants. Our proposed solution implements machine learning algorithms that take the participant\u27s demographic profile and previous smoking behavior into account. We discuss our preliminary evaluation of the system against a couple of pseudo-scenarios and our observation of the system\u27s performance

Building a Tailored Text Messaging System for Smoking Cessation in Native American Populations

When starting new and healthy habits or encouraging vigilance against returning to poor habits, a simple text message can be beneficial. Text messages also have the advantage of being easily accessible for lower-income populations spread over a rural area, who may not be able to afford smartphones with apps or data plans. Users benefit the most from text messages that are customized for them, but personalization requires time and effort on part of the user and the counselor. However, personalization that focuses on the cultural background of a pool of recipients, in addition to general personal preferences, can be a low-cost method of ensuring the best experience for patients interested in taking up new habits. In this paper, we discuss the development of a system for motivating users to quit smoking designed for Native American users in South Dakota, using text messaging as a daily intervention method for patients. Our results show that focusing on modular message customization options and messages with a conversational tone best helps our goal of providing users with customization options that help motivate them to live happy and healthy lifestyles

Symptom Levels in Care-Seeking Bangladeshi and Nepalese Adults With Advanced Cancer

Purpose Three-fourths of patients with advanced cancer are reported to suffer from pain. A primary barrier to provision of adequate symptom treatment is failure to appreciate the intensity of the symptoms patients are experiencing. Because data on Bangladeshi and Nepalese patients’ perceptions of their symptomatic status are limited, we sought such information using a cell phone questionnaire. Methods At tertiary care centers in Dhaka and Kathmandu, we recruited 640 and 383 adult patients, respectively, with incurable malignancy presenting for outpatient visits and instructed them for that single visit on one-time completion of a cell phone platform 15-item survey of questions about common cancer associated symptoms and their magnitudes using Likert scales of 0 to 10. The questions were taken from the Edmonton Symptom Assessment System and the Brief Pain Inventory instruments. Results All but two Bangladeshi patients recruited agreed to study participation. Two-thirds of Bangladeshi patients reported usual pain levels ≥ 5, and 50% of Nepalese patients reported usual pain levels ≤ 4 (population differences significant at P \u3c .001). Conclusion Bangladeshi and Nepalese adults with advanced cancer are comfortable with cell phone questionnaires about their symptoms and report high levels of pain. Greater attention to the suffering of these patients is warranted

A Culturally Tailored Intervention System for Cancer Survivors to Motivate Physical Activity

It is necessary for a cancer survivor to have good health behavior. Essential exercise and proper diet are helpful to decrease the risk of recurrence of the disease and the development of a new cancer type. People from low socioeconomic status are more likely to participate in risky health behaviors and have a higher chance of recurrence of cancer. It is important to have a motivational system for cancer survivors that motivates them to perform regular physical activities. In this article, we discuss the development of an mHealth system, which aims to increase physical activity in Native American populations with culturally appropriate motivational text and video messages. The system also includes an e-journal to monitor and maintain proper healthcare. We will also analyze the pilot data to evaluate the usability and the effectiveness of the system

Reality Versus Grant Application Research “Plans”

This article describes the implementation of the American Indian mHealth Smoking Dependence Study focusing on the differences between what was written in the grant application compared to what happened in reality. The study was designed to evaluate a multicomponent intervention involving 256 participants randomly assigned to one of 15 groups. Participants received either a minimal or an intense level of four intervention components: (1) nicotine replacement therapy, (2) precessation counseling, (3) cessation counseling, and (4) mHealth text messaging. The project team met via biweekly webinars as well as one to two in-person meetings per year throughout the study. The project team openly shared progress and challenges and collaborated to find proactive solutions to address challenges as compared to what was planned in the original grant application. The project team used multiple strategies to overcome unanticipated intervention issues: (1) cell phone challenges, (2) making difficult staffing decisions, (3) survey lessons, (4) nicotine replacement therapy, (5) mHealth text messages, (6) motivational interviewing counseling sessions, and (7) use of e-cigarettes. Smoking cessation studies should be designed based on the grant plans. However, on the ground reality issues needed to be addressed to assure the scientific rigor and innovativeness of this study

Seeing Beyond Visibility: A Four Way Fusion of User Authentication for Efficient Usable Security on Mobile Devices

Security and usability plays an important role in the success in today\u27s computer, mobile, and technology based system. In these systems, security gets higher priority for high security measures ignoring the fact that the system may lead to an unusable one. However, everyday technology users need a system that is usable and also safe. In this paper, we propose a novel approach for usable security for mobile system i.e. a mobile system that will be usable and also secured. Traditional mobile device authentication techniques do not consider the combination of user biometrics, environmental information, and information provided by the sensors within the pervasive system. In this paper, we present a four way fusion of user authentication techniques for efficient usable security on mobile devices. In this approach user is not required to remember any alphanumeric password. The location traces, gait pattern, emotion of user and context of an image is used as metric for authentication. This system silently does authentication using location traces and gait pattern of its user. If the silent authentication fails then system authenticates its users based on user\u27s emotion sequence and an image context previously stored by the user. Our proposed fusion based authentication technique can be useful for numerous real life scenarios where mobile device security is important

A Mobile Survey Tool for Smoking Dependency Among Native Americans

Smoking and tobacco related cancers are very common among Native Americans. Gathering information during different phases of smoking cessation can help us understand different factors that may work during smoking cessation. In this paper, we will present a survey system designed to collect data for several phases of smoking cessation. We designed and developed a survey system that helps researchers to collect data from people who are going through different phases of smoking cessation. We evaluate this system from the experiences of end users and by generating reports