Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Data mining of a remote behavioral tracking system for Type 2 Diabetes patients: A prospective, cohort study

Background: Complications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software. Objective: Associations were evaluated between the smartphone monitoring of health behaviors and HbA1c reductions in a patient subsample with type 2 diabetes who demonstrated clinically significant benefits after participation in a randomized controlled trial. Methods: A priori association-rule algorithms, implemented in the C language, were applied to app-discretized use data involving three primary health behavior trackers (exercise, diet, and glucose monitoring) from 29 participants who achieved clinically significant HbA1c reductions. Use was evaluated in relation to improved HbA1c outcomes. Results: Analyses indicated that nearly a third (9/29, 31%) of participants used a single tracker, half (14/29, 48%) used two primary trackers, and the remainder (6/29, 21%) of the participants used three primary trackers. Decreases in HbA1c were observed across all groups (0.97-1.95%), but clinically significant reductions were more likely with use of one or two trackers rather than use of three trackers (OR 0.18, P=.04). Conclusions: Data mining techniques can reveal relevant coherent behavior patterns useful in guiding future intervention structure. It appears that focusing on using one or two trackers, in a symbolic function, was more effective (in this sample) than regular use of all three trackers.The authors would like to thank NexJ Systems Inc. for their partnership in this trial and for the use of the Connected Wellness Platform as a clinical research tool. Funding was provided by the Public Health Agency of Canada and the Federal Development Agency of Southern Ontario. We offer special thanks to the staff of the Black Creek Community Health Centre and trial participants from the Jane-Finch community of Toronto, Ontario. Joel Katz is supported by a Canadian Institutes of Health Research Canada Research Chair in Health Psychology. The authors would like to acknowledge with sadness the untimely passing of study co-author, colleague, and friend, Dr. Nicholas Cercone. Dr. Cercone’s expertise and mentorship on data mining theory and technique was invaluable. His inspiring and supportive presence will be deeply missed

Acceptability Of Fitbit For Physical Activity Tracking Within Clinical Care Among Men With Prostate Cancer

Prior research has not examined the acceptability of commercially available fitness tracking devices in men with prostate cancer, many of whom are at risk for conditions that physical activity could alleviate. We conducted an exploratory 3- week field study to examine acceptability of the Fitbit Zip and attitudes towards integrating fitness tracking into clinical care among men with prostate cancer. Twenty-six men used the Fitbit Zip for a one-week baseline phase followed by a 2- week optional use phase and then completed in-depth interviews. Interview data was analyzed using inductive thematic analysis. Participants found the device comfortable and easy to wear. Barriers to use included health and technology difficulties. Participants expressed value in sharing Fitbit data with their health care team. Findings support the use of easy to use and simple fitness trackers among men with prostate cancer and there could be opportunities to integrate fitness tracker data into clinical care

LAYING THE GROUNDWORK: FITNESS TRACKER SECURITY FOR USE BY DEPARTMENT OF THE NAVY PERSONNEL

Bluetooth-capable Internet of Things devices have become prevalent within modern society and continuous connectivity has become an expectation. Recently, wearable fitness trackers have been authorized for use by service members while in uniform. The objective of this work was to determine if vulnerabilities persist in fitness trackers and if their ecosystems render them a security risk to the Department of Defense. The devices selected for this study were readily available, low-cost products, spanning several vendors. Five device models were selected from among the following vendors: Huawei, Amazfit, Garmin, and Fitbit. These devices use Bluetooth to transmit sensitive data to the paired central device. This Bluetooth traffic was captured from two separate perspectives, through passive eavesdropping and directly from the central device. This Bluetooth traffic was captured from two perspectives. The traffic was captured passively, using Project Ubertooth, and actively, logged on the central device, as the devices conducted pairing and various feature invocations. The resulting packet capture files were analyzed to determine vendor-specific security implementation and to determine susceptibility to attack. Three of the five devices studied, those from Huawei and Amazfit, utilized no Bluetooth security features. They did not conduct pairing and routinely operated in the most vulnerable stage of Bluetooth communication. This poses significant risk to the user.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

The Internet of Hackable Things

The Internet of Things makes possible to connect each everyday object to the Internet, making computing pervasive like never before. From a security and privacy perspective, this tsunami of connectivity represents a disaster, which makes each object remotely hackable. We claim that, in order to tackle this issue, we need to address a new challenge in security: education

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised

Breaking Fitness Records without Moving: Reverse Engineering and Spoofing Fitbit

Tens of millions of wearable fitness trackers are shipped yearly to consumers who routinely collect information about their exercising patterns. Smartphones push this health-related data to vendors' cloud platforms, enabling users to analyze summary statistics on-line and adjust their habits. Third-parties including health insurance providers now offer discounts and financial rewards in exchange for such private information and evidence of healthy lifestyles. Given the associated monetary value, the authenticity and correctness of the activity data collected becomes imperative. In this paper, we provide an in-depth security analysis of the operation of fitness trackers commercialized by Fitbit, the wearables market leader. We reveal an intricate security through obscurity approach implemented by the user activity synchronization protocol running on the devices we analyze. Although non-trivial to interpret, we reverse engineer the message semantics, demonstrate how falsified user activity reports can be injected, and argue that based on our discoveries, such attacks can be performed at scale to obtain financial gains. We further document a hardware attack vector that enables circumvention of the end-to-end protocol encryption present in the latest Fitbit firmware, leading to the spoofing of valid encrypted fitness data. Finally, we give guidelines for avoiding similar vulnerabilities in future system designs