ME310 Design Innovation at Staford University

Need statement

The older adult population worldwide is growing. What is uncertain and cannot be predicted easily is whether or not advances in medicine and science can maintain pace with life expectancy. If we are expected to live longer but medicine falls short, then we can expect that we will feel the effects of aging on our bodies and on our lifestyles and will have to live with them for much longer than we do today. Thus, there is an urgent need to develop technology solutions for the older adult population which will allow them to experience the aging process in comfort and in such a way that is acceptable to their independent lifestyles. Among these need areas is the area of health and medication-taking. Older adults have to take a cocktail of medications that range in varying degrees of complexities. These medications aim to improve or sustain the health of an older adult, yet older adults often find this necessary component of their health difficult to maintain and complex to manage.

Problem statement

To maintain their health and vitality, older adults are often required to take a number of medications and supplements. The typical medication routine usually occurs at least twice daily with upwards of 8-15 pills being ingested, though oftentimes the routine is more complex and the pills more numerous. Though this routine is important and critical to older adults’ continued healthy lifestyles, it is an unpleasant and time consuming process that is easily forgettable and prone to errors and that reminds them of their declining health state and detracts from their quality of life. Our goal is to offer a redesign of the medication taking experience at home by simplifying older adults’ interaction with their medication (i.e. pill sorting) and integrating smart solutions into their pill-taking that will allow them to continue to be mobile and active without missing a medication or worrying about it. The purpose of this redesign is to allow older adults to positively reframe their home medication taking experience. Simplifying the medication-taking process presents a compelling area of technological solutions to create assurance and confidence for an older adult who lives independently and has to take a cocktail of medications. There are some point solutions on the market that address the complexity and management of medications, but none that combine point solutions to address the entire medication-taking space. The objective is to design and develop a technological solution for older adults that will enhance their independent living situation by increasing their self-efficacy around medication-taking.


Medi Design

After interviews with older adults, we learned that older adults also love beautiful things. Overall, we avoided sharp edges and designed Medi Home with smooth curves to give an organic feel to the home device. We wanted to make sure that Medi home fit into an older adult’s lifestyle. The User interface presents a 45-degree tilt, so that the older adult can easily operate and read information from Medi Home. Older adults gradually lose the ability to identify colors, so Medi Home intentionally uses black on white font to create color contrast. Finally, the Medi Go keychain is designed with one large button to make the intention of the keychain very clear.

The final pill pack design is a parallelogram that fits around a 2.5 inch by 2.5 inch square of plastic with the end of one side folded over as a tab for peeling the plastic away from the paper. The bottom side is shaded so that the user knows that the peeling should happen on the bottom. The face of each pack has the pack number and the day, and indicates by icon what time of day the pack corresponds to. It also lists the medications in the pack. Each pack is attached to the others with a slit cut for easy tearing. We used an impulse sealer to melt the plastic of the bag to the plastic side of the paper backing, thus allowing the packs to be sealed.

Ci-Jyun Polar Liang
Ci-Jyun Polar Liang
Assistant Professor (Jan 2024)

My research interests include Human-Robot Collaboration, Computer Vision, Reinforcement Learning, BIM, Digital Twins, and Extended Reality.