PRE2023 3 Group7

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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

Minutes meeting 23-02-2024

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


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

Literature research Sven

Literature Review Fenna

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 meeting and evaluation (1h)
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)