Assembly of New Amulet “Kite.d” Boards Moves Forward

This spring, with a stabilized design code-named “Kite.d”, the Amulet team specified a new board and case design for the latest Amulet revision. Team members Ron Peterson and Taylor Hardin delivered the designs to New Hampshire’s DataEd, and with their assistance facilitated the fabrication of 150 Amulet Kite.d main- and daughter-boards. DataEd facilitated basic electrical testing of the design before delivery, and now that we’ve received them, the team is busy assembling the latest round of Amulets for upcoming studies. Check out some on-site pictures below!

DSCN0791Parts being placed on 6 Amulet Kite.d boards

DSCN0802A technician tests assembled boards for electrical soundness

DSCN0801Amulet team member Taylor Hardin tests functional capabilities of a new unit

Amulet Team Brings Paper to USENIX


Last month in Boston at the annual USENIX conference, the Amulet team’s most recent paper was selected for presentation. Entitled “Application Memory Isolation on Ultra-Low-Power MCUs”, the paper explores increasing the security level of the Amulet platform, through novel uses of memory protection and isolation. To read more, click through to the PDF below.

PDF: Application Memory Isolation on Ultra-Low-Power MCUs

George Boateng Featured In Dartmouth News

This week, Amulet researcher George Boateng was lauded in the Dartmouth News. George, who received both his masters and his undergrad degrees from Dartmouth, is now a staff researcher on the Amulet project. In addition to outlining George’s recent awards for his entrepreneurial efforts, the article also delves into his work with Amulet PI David Kotz, and how Amulet was a significant part of George’s academic career. To read more, click below.

Dartmouth News: Exploring Applications of Technology in Health and Wellness

Annual Amulet Retreat 2017


This past week, some members of the Amulet team gathered at Dartmouth College in Hanover, NH for the annual Amulet retreat. Activities included brainstorming new Amulet applications, prioritizing tasks for the coming year, and finalizing the latest Amulet hardware revision. (From left: Gunnar Pope, Byron Lowens, Ryan Halter, Vivian Motti, Ryan Scott, Dave Kotz, Taylor Harding, George Boateng, Varun Mishra, John Batsis, Ron Peterson, Jacob Sorber, Patrick Proctor)

Wearable Privacy: Skeletons in the Data Closet

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
photo of Byron Lowens presenting his paper, "Wearable Privacy: Skeletons in the Data Closet" at ICHI 2017

Byron presenting his paper, “Wearable Privacy: Skeletons in the Data Closet” at ICHI 2017

Amulet paper at UbiTtention/Ubicomp

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.

Amulet poster at MobiSys

Taylor Hardin presented a poster at ACM MobiSys conference this week, about some clever new ideas for protecting the memory inside an MSP430 when mutually-untrusted apps have to share the same small memory.  Abstract below.


Taylor Hardin explains his work to attendees at MobiSys.

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Amulet 1.1

We’ve just released a version 1.1 of the hardware, with many fixes and improvements; see our GitHub site.

  • Changed from spring terminals to SPI-BI-WIRE POGO pin connector for programming both the MSP430 and nRF51822
  • Repositioned the LCD screen to provide more room for the programmer ports and LEDs
  • Broke out UART TX/RX lines for debugging the nRF51822
  • Complete case redesign to better fit the mother-daughter boards, buttons, and LCD screen
  • Replaced the 4 pin charging connector with a more sturdy USB charging port


Cryptographic transfer of sensor data from the Amulet to a smartphone

David Harmon ’17 develops and evaluates a novel protocol for secure transfer of sensor data from an Amulet to a smartphone, in this Senior Honors Thesis released as a Dartmouth Computer Science Technical Report.

Abstract. The authenticity, confidentiality, and integrity of data streams from wearable healthcare devices are critical to patients, researchers, physicians, and others who depend on this data to measure the effectiveness of treatment plans and clinical trials. Many forms of mHealth data are highly sensitive; in the hands of unintended parties such data may reveal indicators of a patient’s disorder, disability, or identity. Furthermore, if a malicious party tampers with the data, it can affect the diagnosis or treatment of patients, or the results of a research study. Although existing network protocols leverage encryption for confidentiality and integrity, network-level encryption does not provide end-to-end security from the device, through the smartphone and database, to downstream data consumers. In this thesis we provide a new open protocol that provides end-to-end authentication, confidentiality, and integrity for healthcare data in such a pipeline.

We present and evaluate a prototype implementation to demonstrate this protocol’s feasibility on low-power wearable devices, and present a case for the system’s ability to meet critical security properties under a specific adversary model and trust assumptions.

Advisor: David Kotz.

ActivityAware: Wearable System for Real-Time Physical Activity Monitoring among the Elderly

George Boateng, M.S., reports on new Amulet research in his Master’s thesis, available as a Dartmouth Computer Science Technical Report.

Abstract. Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person’s daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application on the Amulet wrist-worn device that monitors the daily activity levels (low, moderate and vigorous) of older adults in real-time. The app continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day’s accumulated time spent at that activity level, displays the results on the screen and logs summary data for later analysis.

The app implements an activity-level detection model we developed using a Linear Support Vector Machine (SVM). We trained our model using data from a user study, where subjects performed common physical activities (sit, stand, lay down, walk and run). We obtained accuracies up to 99.2% and 98.5% with 10-fold cross validation and leave-one-subject-out (LOSO) cross-validation respectively. We ran a week-long field study to evaluate the utility, usability and battery life of the ActivityAware system where 5 older adults wore the Amulet as it monitored their activity level. The utility evaluation showed that the app was somewhat useful in achieving the daily physical activity goal. The usability feedback showed that the ActivityAware system has the potential to be used by people for monitoring their activity levels. Our energy-efficiency evaluation revealed a battery life of at least 1 week before needing to recharge. The results are promising, indicating that the app may be used for activity-level monitoring by individuals or researchers for epidemiological studies, and eventually for the development of interventions that could improve the health of older adults.

Advisors: David Kotz, Ryan Halter, John Batsis