Junyi Zhu, Liang He, Jun Nishida, Hamid Ghaednia, Hsin-Liu (Cindy) Kao, Jon E. Froehlich, Edward Wang, Stefanie Mueller.
Towards More Personal Health Sensing
In Proceedings of CHI 2022 Special Interest Group.

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Time: Wednesday, May 4th, from 2:15pm - 3:30pm CDT
   (New Orleans local time)

In-person Location: Room 387

Hybrid Location:

Towards More Personal Health Sensing

With the development of low-cost electronics, rapid prototyping techniques, as well as widely available mobile devices (e.g. mobile phones, smart watches), projects related to the design and fabrication of personal health sensing applications, either on top of existing device platforms (e.g. mHealth), or as stand-alone devices, have emerged in the last decade. In addition, recent advances in novel sensing and interface technologies, accessibility studies and system design open up new possibilities and can bring in different perspectives for personal health sensing. We believe that joining the forces in such interdisciplinary work is a key to moving the field of personal health sensing forward. This Special Interest Group aims to bring in researchers from different fields, identify the significance and challenges of the personal health sensing domain, discuss potential solutions and future research directions, and promote collaborative research opportunities.


With the development of low-cost electronics, rapid prototyping techniques, as well as widely available mobile devices (e.g. mobile phones, smart watches), projects related to the design and fabrication of personal health sensing devices and applications have emerged in the last decade. These projects are usually either built on top of existing device platforms, such as mobile phones (e.g. HemaApp [20], Seismo [21]) and smart watches (e.g. Ravichandran et al. [17]), or as stand-alone devices (e.g. Glabella [7], DoppleSleep [16], EIT-kit [23]). Recently, with the assistance of interactive device prototyping tools, such as CurveBoards [22], SqueezaPulse [6] and MorphSensor [24], as well as widely available personal fabrication machines [1], users with limited electronics knowledge can also design and fabricate customized health sensing devices, which opens up opportunities for the field of personal health sensing.

However, there are more interdisciplinary research topics that can be applied to personal health sensing. For example, works about novel sensing and interface technologies increase the design space and provide novel sensing techniques that can be integrated into personal health sensing devices, such as kinesthetic sensing (bioSync [14], Kasahara et al. [12]), smell sensing (Brooks et al. [3]) skin interfaces (SkinMorph [9], SkinWire [10]), and even some unconventional on-body interfaces like fingernail interfaces (NailO [11]). In addition, well-evaluated accessibility studies, like accessibility for blind and low vision people [13, 15], as well as for d/Deaf and hard of hearing (DHH) people [5, 8], can be considered as design guidelines for future personal health sensing devices.

Another perspective that is often overlooked is the design of personal health sensing devices. Apart from the "functional" aspect of the device design, such as customizing the shape for ensuring constant contact to the measured area [2], and altering measuring locations for capturing better biomedical signals [19], the form factors and appearance of the device also have impacts over user’s self-esteem and even mental health [18]. Like other everyday personal belongings, personal health sensing devices design should consider user’s artistic needs and the effects on the user’s mental state. Instead of being rigid and box-like, they can also be unobtrusive, or be part of the user’s personal decoration and social expression.

In this SIG, we will be discovering these potential research spaces, and building an interdisciplinary network of researchers to bring solutions and new perspectives into the personal health sensing domain. We will use this SIG as a platform to learn about each other’s work — the challenges, tools and techniques being used, and discuss if and how they can be applied to personal health sensing. We believe that joining the forces in such interdisciplinary work is a key to moving the field of personal health sensing forward.


In this SIG about personal health sensing, we aim to:

  • define the term personal health sensing and discuss how it relates to (and differentiates from) traditional health sensing and other research disciplines in HCI;
  • identify the core aspects of personal health sensing and define the open challenges / opportunities, such as the device form factors, personalized sensing interfaces, acquisition of ground truth data, clinical trials, device feedback that respects a user’s intention / voluntary, user privacy, applicable novel sensing and fabrication technologies etc.;
  • vote for the top identified opening challenges with participants and collaboratively brainstorm solutions;
  • summarize potential future research directions in personal health sensing and promote collaborative research opportunities.

This process will involve open discussions with attendees. During the session, we will ask attendees to share their own diverse backgrounds, experiences, and opinions to get a broad picture of what personal health sensing means to the community. We will then hold small group discussions to identify the core challenges of personal heath sensing and brainstorm solutions, which will then be shared with the entire audience. We will vote on the most important challenges identified in the small group discussions through online voting platforms (e.g. Slido [4]), so that attendees can participate both physically and virtually with their preferred devices. We hope to compose a summary of this SIG and submit it to a future CHI conference as a workshop or a journal position paper to reach the broader community and create further engagement. We are welcoming both experienced health sensing related researchers and new-comers to participant this SIG.


This SIG is targeted at researchers that work in fields related to personal health sensing, and those who have general interests in the topics. To align the composition of the organizing team with the goals of the SIG and attract researchers from related fields, the main organizers Junyi Zhu and Stefanie Mueller have already reached out to researchers of related disciplines and invited them to join the SIG organization, such as Edward Wang from the health sensing domain, Liang He from personal fabrication, Hamid Ghaednia from the medical field, Jun Nishida from sensing and interface technologies, Hsin-Liu (Cindy) Kao with design expertise, as well as Jon Froehlich who focuses on accessibility studies. The organizers will act as "hosts" for their respective fields, i.e. they will provide an overview of research from their discipline and how it relates to personal health sensing. In addition, they will help to distribute this SIG among their disciplines to attract participants, as well as connect HCI researchers with potential collaborators in their field.

The SIG will be held under the hybrid format to enable both physical and virtual attendees to join. However, all participants are encouraged to attend physically when possible for the most interactive experience. Our SIG welcomes both experienced health sensing researchers who wish to develop the field further, and new-comers looking to get a taste for the field.


The SIG will be held under the hybrid format in which attendees can participate both physically and remotely. For remotely-attending participants, we will have a Zoom link that streams the SIG in real time. Remote participants will also be assigned to breakout rooms for small group discussion sessions. For selecting the core aspects and most significant challenges, remote participants can use the online voting system in the same way as the physical attendees on their own devices.

We propose the following 75-minute agenda:

  • Introduction: We will begin with an overview of personal health sensing, rapid 1-minute introductions of the co-organizers and their work related to personal health sensing, and an ice-breaker activity. (15 minutes)
  • Small Group Brainstorm (core aspects & challenges): We will then break into small groups to brainstorm and discuss the core aspects and challenges in the area of personal health sensing. Each group will be seeded with a separate list of initial ideas (i.e. the ones mentioned in Section 2) to ensure topic coverage. (15 minutes)
  • Present & Discuss: Each group will present its results to the entire SIG and lead a small discussion. We will take notes of the identified challenges, and set up an online voting system for all participants to select the most significant ones. (15 minutes)
  • Small Group Brainstorm (solutions & opportunities): Once all groups have presented and voting has closed, attendees will focus on the top ∼5 key challenges and again split into small groups (same groups as previous brainstorm session) to discuss solutions and potential opportunities. We will provide a Google Docs / Slides for each group to document the discussion. (15 minutes)
  • Closing Discussion: We will reconvene as the entire SIG and review potential solutions and key future research topics in the field of personal health sensing as identified in the small group discussions. Organizers will provide access to a Slack group for further discussion. (15 minutes)


We expect this SIG to influence and establish future research directions in the area of personal health sensing. We hope to bring in researchers from different fields, form connections across disciplines, explore new perspectives of each other’s field, and promote collaborative research opportunities. We will compose a summary of this SIG and submit it to a future CHI conference as a workshop or a journal position paper to reach the broader community and further engagement.


Junyi Zhu (main contact person) is a PhD candidate from MIT CSAIL, HCIE Group, working with professor Stefanie Mueller. He works at the intersection of personal fabrication and health sensing. His recent research focuses on creating personal health sensing devices with rapid function prototyping techniques and novel sensing technologies. His work has received honorable mention award at CHI. He worked as a student volunteer for CHI PC meeting and conference, as well as an associate chair for CHI Late-Breaking Work in the past. He is a 2017 Seneff-Zue Fellow and a 2021 Thomas G. Stockham, Jr (1955) and Bernard (Ben) Gold Fellow.

Liang He is a PhD candidate in Computer Science & Engineering at the University of Washington, advised by Jon E. Froehlich. He works at the intersection of HCI and digital fabrication. His research aims to explore and create augmented 3D printable behaviors (e.g. deformation, actuation, and sensing) that are beyond static shapes and enabled by a set of "print drivers"—flexure-based or texturized 3D printed mechanical structures. He takes a mechanical perspective to create novel design techniques by exploiting parametric mechanical properties and developing computational design tools for the design, control, and fabrication of 3D printable augmented behaviors.

Jun Nishida is a postdoctoral fellow at Human Computer Integration Lab at University of Chicago. He received his PhD in Human Informatics at University of Tsukuba, Japan in 2019. He is interested in exploring interaction techniques where people can communicate their embodied experiences to support each other in the fields of rehabilitation, education, and design. He designs wearable interfaces which share one’s embodied and social experiences among people by means of electrical muscle stimulation, exoskeletons, virtual/augmented reality systems, along with psychological knowledge. He received more than 40 awards including ACM UIST Best Paper Award, Microsoft Research Asia Fellowship Award, and Forbes 30 Under 30 Award.

Hamid Ghaednia is an Instructor at the Department of Orthopaedic Surgery of Harvard Medical School and Co-Director of Center for Physical Artificial Intelligence at Massachusetts General Hospital, which focuses on integration of machine learning and biomedical engineering. His background is in mechanical engineering with extensive experience in developing biomedical and health sensing devices, including the development of custom measurement setups based on electrical impedance tomography technology. He has won several fellowship and awards including two world silver medals and 2nd place in RoboCup.

Hsin-Liu (Cindy) Kao is an Assistant Professor in Design+Environmental Analysis, with graduate field faculty appointments in Information Science, and Electrical & Computer Engineering at Cornell University. She founded and directs the Hybrid Body Lab. Her research practice themed Hybrid Body Craft blends aesthetic and cultural perspectives into the design of on-body interfaces. She also creates novel processes for crafting technology close to the body. She was awarded a National Science Foundation CAREER Award (2021). Her research has received several Honorable Mention/Best Paper Awards in top-tier Computer Science conferences (ACM CHI, UIST, ISWC and DIS). Kao has served as the program chair for ACM International Symposium of Wearable Computers (ISWC).

Jon E. Froehlich is an Associate Professor in the University of Washington, Paul G. Allen School of Computer Science & Engineering. He is a Sloan Fellow, and NSF CAREER Awardee. His research is in Human-Computer Interaction (HCI) with a focus on high-value social domains such as accessibility, environmental sustainability, and STE(A)M education. At University of Washington, He directs the Makeability Lab, works with an extraordinary set of students and collaborators, and teaches CS courses that explore the materiality of computing and the ever-changing relationships between humans, bits, and atoms.

Edward Wang is an Assistant Professor at University of California San Diego, Electrical and Computer Engineering department and the Design Lab. He is affiliated with the UCSD CSE department, Center for Wireless and Population Health Systems (CWPHS), Center for Wearable Systems (CWS), and serve as a Board of Director for the Center for Mental Health Technology (MHTech). He directs the UCSD Ubiquitous Data & Computing Lab. His research focuses on developing new sensing techniques for monitoring a person’s health more continuously, conveniently, and cheaply with a goal of ultimately bringing clinical sensing out of the clinic.

Stefanie Mueller is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science joint with the Department of Mechanical Engineering. Her research focuses on novel fabrication processes and prototyping tools that push the boundaries of personalization and customization of fabricated objects. More recently, Stefanie’s research has focused on tightly integrating sensing with the personalized form factor of objects through fabrication processes, such as 3D printing with conductive materials and silver inkjet printing, to create various interactive objects including customized health sensing devices.