Another recent paper from John Batsis and the Amulet group, highlighting a custom sensor developed by our team and presented at the International Conference on Body Area Networks (ICBAN):
- John A. Batsis, George G. Boateng, Lillian M. Seo, Curtis L. Petersen, Karen L. Fortuna, Emily V. Wechsler, Ronald J. Peterson, Summer B. Cook, Dawna Pidgeon, Rachel S. Dokko, Ryan J. Halter, and David F. Kotz. Development and Usability Assessment of a Connected Resistance Exercise Band Application for Strength-Monitoring. World Academy of Science, Engineering and Technology, 13(5):340-348, June 2019. DOI 10.5281/zenodo.
Abstract: Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting is fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.
The following paper dates to last year, but is an important publication from the Amulet group:
- John A. Batsis, Alexandra Zagaria, David F. Kotz, Stephen J. Bartels, George G. Boateng, Patrick O. Proctor, Ryan J. Halter, and Elizabeth A. Carpenter-Song. Usability evaluation for the Amulet wearable device in rural older adults with obesity. Gerontechnology, 17(3):151-159, 2018. DOI 10.4017/gt.2018.17.3.003.00.
Abstract: Mobile health (mHealth) interventions hold the promise of augmenting existing health promotion interventions. Older adults present unique challenges in advancing new models of health promotion using technology including sensory limitations and less experience with mHealth, underscoring the need for specialized usability testing. We use an open-source mHealth device as a case example for its integration in a newly designed health services intervention. We performed a convergent, parallel mixed-methods study including semi-structured interviews, focus groups, and questionnaires, using purposive sampling of 29 older adults, 4 community leaders, and 7 clinicians in a rural setting. We transcribed the data, developed codes informed by thematic analysis using inductive and deductive methods, and assessed the quantitative data using descriptive statistics. Our results suggest the importance of end-users in user-centered design of mHealth devices and that aesthetics are critically important. The prototype could potentially be feasibly integrated within health behavior interventions. Centralized dashboards were desired by all participants and ecological momentary assessment could be an important part of monitoring. Concerns of mHealth, including the prototype device, include the device’s accuracy, its intrusiveness in daily life and privacy. Formative evaluations are critically important prior to deploying large-scale interventions.
Today we presented an “Experience” paper at ACM MobiCom, summarizing the technology, the studies, and the challenges and lessons learned over seven years of research.
George Boateng, Vivian Genaro Motti, Varun Mishra, John A. Batsis, Josiah Hester, and David Kotz. Experience: Design, Development and Evaluation of a Wearable Device for mHealth Applications. In Proceedings of the International Conference on Mobile Computing and Networking (MobiCom), October 2019. DOI 10.1145/3300061.3345432.
Abstract: Wrist-worn devices hold great potential as a platform for mobile health (mHealth) applications because they comprise a familiar, convenient form factor and can embed sensors in proximity to the human body. Despite this potential, however, they are severely limited in battery life, storage, bandwidth, computing power, and screen size. In this paper, we describe the experience of the research and development team designing, implementing and evaluating Amulet? an open-hardware, open-software wrist-worn computing device? and its experience using Amulet to deploy mHealth apps in the field. In the past five years the team conducted 11 studies in the lab and in the field, involving 204 participants and collecting over 77,780 hours of sensor data. We describe the technical issues the team encountered and the lessons they learned, and conclude with a set of recommendations. We anticipate the experience described herein will be useful for the development of other research-oriented computing platforms. It should also be useful for researchers interested in developing and deploying mHealth applications, whether with the Amulet system or with other wearable platforms.
John Batsis and the Amulet team just published a paper regarding Use of Amulet in behavioral change for geriatric obesity management.
Background: Obesity in older adults is a significant public health concern. Weight-loss interventions are known to improve physical function but risk the development of sarcopenia. Mobile health devices have the potential to augment existing interventions and, if designed accordingly, could improve one’s physical activity and strength in routine physical activity interventions. Methods and results: We present Amulet, a mobile health device that has the capability of engaging patients in physical activity. The purpose of this article is to discuss the development of applications that are tailored to older adults with obesity, with the intention to engage and improve their health. Conclusions: Using a team-science approach, Amulet has the potential, as an open-source mobile health device, to tailor activity interventions to older adults.
John A. Batsis, Alexandra B. Zagaria, Ryan J. Halter, George G. Boateng, Patrick Proctor, Stephen J. Bartels, and David Kotz. Use of Amulet in behavioral change for geriatric obesity management. Journal of Digital Health, 5, June 2019. DOI 10.1177/2055207619858564.
David Kotz recently presented a paper titled Amulet: an open-source wrist-worn platform for mHealth research and education.
Abstract: The advent of mobile and wearable computing technology has opened up tremendous opportunities for health and wellness applications. It is increasingly possible for individuals to wear devices that can sense their physiology or health-related behaviors, collecting valuable data in support of diagnosis, treatment, public health, or other applications. From a researcher’s point of view, the commercial availability of these “mHealth” devices has made it feasible to conduct scientific studies of health conditions and to explore health-related interventions. It remains difficult, however, to conduct systems work or other experimental research involving the hardware, software, security, and networking aspects of mobile and wearable technology. In this paper we describe the Amulet platform, an open-hardware, open-software wrist-worn computing device designed specifically for mHealth applications. Our position is that the Amulet is an inexpensive platform for research and education, and we encourage the mHealth community to explore its potential.
In Workshop on Networked Healthcare Technology (NetHealth), pages 891-897, January 2019. IEEE Computer Society Press.
Amulet was mentioned in a recent podcast featuring Professor Kelly Caine, of Clemson University.
A new paper from the extended Amulet group.
John A. Batsis, John A. Naslund, Alexandra B. Zagaria, David Kotz, Rachel Dokko, Stephen J. Bartels & Elizabeth Carpenter-Song. Technology for Behavioral Change in Rural Older Adults with Obesity. Journal of Nutrition in Gerontology and Geriatrics, April 2019.DOI: 10.1080/21551197.2019.1600097
David Kotz recently presented an invited webinar lecture in the Mobile Data to Knowledge (MD2K) program. The first half of that lecture provides an overview of the Amulet project and our research using the Amulet. (The second half describes the Auracle project – also worth checking out!)
Equipped with sensors that are capable of collecting physiological and environmental data continuously, wearable technologies have the potential to become a valuable component of personalized healthcare and health management. However, in addition to the potential benefits of wearable devices, the widespread and continuous use of wearables also poses many privacy challenges. In some instances, users may not be aware of the risks associated with wearable devices, while in other cases, users may be aware of the privacy-related risks, but may be unable to negotiate complicated privacy settings to meet their needs and preferences. This lack of awareness could have an adverse impact on users in the future, even becoming a “skeleton in the closet.” In this work, we conducted 32 semi-structured interviews to understand how users perceive privacy in wearable computing. Results suggest that user concerns toward wearable privacy have different levels of variety ranging from no concern to highly concerned. In addition, while user concerns and benefits are similar among participants in our study, these variablesshould be investigated more extensively for the development of privacy enhanced wearable technologies.
- Byron Lowens, Vivian G. Motti, and Kelly E. Caine. Wearable Privacy: Skeletons in the Data Closet. Proceedings of IEEE International Conference on Healthcare Informatics (ICHI). Park City, UT, 2017, pp. 295-304. DOI: 10.1109/ICHI.2017.29
Byron presenting his paper, “Wearable Privacy: Skeletons in the Data Closet” at ICHI 2017
Abstract: In this work, we attempt to determine whether the contextual information of a participant can be used to predict whether the participant will respond to a particular EMA trigger. We use a publicly available dataset for our work, and find that by using basic contextual features about the participant’s activity, conversation status, audio, and location, we can predict if an EMA triggered at a particular time will be answered with a precision of 0.647, which is significantly higher than a baseline precision of 0.41. Using this knowledge, the researchers conducting field studies can efficiently schedule EMAs and achieve higher response rates.
Varun Mishra, Byron Lowens, Sarah Lord, Kelly Caine, and David Kotz. Investigating Contextual Cues As Indicators for EMA Delivery. In Proceedings of the International Workshop on Smart & Ambient Notification and Attention Management (UbiTtention), pages 935-940, September 2017. ACM. DOI 10.1145/3123024.3124571.