PRE2023 3 Group7: Difference between revisions
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Revision as of 16:58, 25 February 2024
Pill dispensing robot
Team and interests
Quinten Liu, 1842471, q.m.liu@student.tue.nl
Fenna Sigmond, 1696947, f.e.sigmond@student.tue.nl
Thijs Frints, 1441523, t.g.g.frints@student.tue.nl
Daniel Joaquim Ho, 1534254, d.joaquim.ho@student.tue.nl
Sven de Gruyter, 1857657, s.d.gruyter@student.tue.nl Sjoerd van de Goor, 1557815, s.v.d.goor@student.tue.nl
Interests:
- Medical Imaging
- Physical product
- AI
- Tangible / functional product
- Danger detection or prevention
- Healthcare or elderly care
Meetings
Target Audience
Households with one (or more) people that have trouble consistently taking and understanding their medicine. (Elderly people that live by themselves and have trouble taking and managing their medication.)
Stakeholders and their interests
To identify the problem statement certain stakeholders and their interests in the pill dispensing robot are identified using literature (and interviews).
Elderly
Elderly people living by themselves can have trouble taking medication on the right time and are insecure about their management of their medication. The pill dispensing robot can help them increase their medication adherence, by making a planning for them for taking the medication on the right time, getting notifications on when to take medications, instructions for taking their medications, and answering questions they might have.
Informal caregivers
The caregivers that help the elderly managing their medication are not always present to answer questions and do not always know if the medications are taken the right way and at the right time. The pill dispensing robot can help their administration so they can assist the elderly people. Also if they are not around, the robot can answer questions instead of them.
General practitioner
The robot could help the GP get better insight in the medical administration.
Product Overview
A robot which dispenses pills on a specific schedule and can inform about and answer questions about medical usage, which may be interacted with by speech, and buttons, and which talks back and provides subtitles on the spoken texts using a screen.
Preliminary Functional Requirements
Software
- AI integration to understand speech
- AI integration to process natural language inquiries about medicine in the specific context of the patient
- AI integration to process natural language outputs to spoken language
- Software to memorize and on time inform about medicine intake
- Remember which medicine was taken
- Admin-client distinguishment in access to schedule
Hardware
- Easily swappable medicine cartridges for about 4 types of medicine
- Dispensing function
- Speaker, screen, microphone, buttons
- Small and light
- Probably stationary
- Non-intrusive
Informal planning
Week 1 | Week 2 | Week 3 | Week 4 | ||||
---|---|---|---|---|---|---|---|
Literature review + summaries
Relevant groups’ work |
A
|
Literature discussion
Functional requirements Target audience & problem |
A | Designing
Preliminary software Components + feedback + order needed |
Finalize components
Software prototype 3D modelling of product |
||
Week 5 | Week 6 | Week 7 | Week 8 | ||||
Software done
Assembly done 3D Printing done |
Iterate on software or add app
Solve problems |
Solve problems
Prepare presentation Begin cleaning up wiki |
Present
Clean up wiki |
A = All, Q = Quinten, F = Fenna, T = Thijs, D = Daniel, Sv = Sven, Sj = Sjoerd
Literature reviews (Paste all articles here eventually)
Goals of review:
- Find state of the art
- Find what was done; what worked, what did not work. Perhaps reach out to the members of groups of previous years to ask for further details
- Medical technology state
- Pill dispensing specifics
- Elderly technology interaction
- Privacy and ethics of the technology
Literature Review of already existing medicine dispensers
Existing Products, Specifications, and Research and Regulation
General Literature Review of comparisons, effectiveness, and ethics regarding MAPs
Time spent
Week 1:
All | 1st meeting (2h) |
Quinten | Researching SotA (2h); Finding and reading relevant papers regarding medication dispensers (3h); Finding and reading relevant papers regarding ethics and elderly care (2h) |
Fenna | Research State of the Art (1h); Robot specifications (2h); Research Product Design (1h); Research Use Case (2h) |
Thijs | Looking at already functioning medicine dispensers (1.5h); Reading papers on dispensing robots and summarizing them (4.5h); look at ethics for medication rules (0.5) |
Daniel | Research what has been done/state of the art (3.5hr); Dispensing Specifications (1.5hrs); EU regulations, medical technology state, privacy and ethics of the tech (3.5hr); |
Sven | Research on state of the art/dispenser mechanisms (1,5h); Research AI implementation by notifications (1,5h), naming requirements/specifications (1h) |
Sjoerd | Setup wiki (2h); process annotations of first meeting (1.5h); Read documentation OpenAI and Google for insight into which we can use (3h) |
Week 2:
All | Feedback Monday meeting and evaluation (1h), Meeting 23-2-24 (1h) see minutes |
Quinten | |
Fenna | Privacy Research |
Thijs | |
Daniel | |
Sven | start identifying stakeholders and specifying the target audience (1,5h) |
Sjoerd | Create prototype AI implementation, with testing and prompt engineering, using API documentation (4h) |