NON-DEMANDING CUSTOM HAND SPLINT
Context
When
January - May 2018
Who
Victor Bell, Kate Doherty, Gavin Hegarty, Vincent
O'Donoghue, Daniel Rodríguez Rodríguez, Amjad Yousif
Where
Biomedical Design Project course
Trinity College Dublin and St. James's Hospital, Dublin (Ireland)
Trinity College Dublin and St. James's Hospital, Dublin (Ireland)
Why
Elderly patients with dementia may manifest a hand
contracture reflex. Traditional hand splints require heat to
become pliable and fit the patient’s hand shape. However,
dementia makes patients sensitive to hot materials and it is
hard for them to provide feedback during the fitting
procedure. Our mission was to design a comfortable and
supporting hand splint that could be simply sized and used
by these types of patients, without the need for their
feedback.
Research
To familiarize ourselves with the clinical aspects of a
hand contraction reflex and understand the needs of
patients, we analyzed commercial hand splints and interviewed an Occupational Therapist at St James's Hospital in Dublin, Bronagh Flynn. Bronagh also served as a guide in the later Ideation and
Prototyping phases.
We identified the following patient needs:
We identified the following patient needs:
1
Well shaped
The splint should be shaped after the patient’s hand to provide proper support.2
The right touch
The splint should be soft to their touch, but rigid enough to withstand their grip.3
No participation
The patient's participation should be minimal during the process.4
Low-cost
The splint should be made of inexpensive materials, be easily washable and replaceable.Ideation
We split ideation into two parallel tracks, each answering a
burning question:
1) How might we design a splint that can stop a hand contracture reflex from getting worse?
Inflatable Balloon
Molded Splint
Curving Pad
Velcro-Palm SplintOur teammate Vincent illustrated the more developed concepts
we came up with. We were fond of the inflatable balloon idea,
but it was also the riskier to build. The Velcro idea was
simple to execute but we found it would be difficult to find a
material that could be flexible AND rigid. We went forward
with the curving pad and molded splint ideas.
1) How might we design a splint that can stop a hand contracture reflex from getting worse?
2) How might we know the patient's hand dimensions so as to
make a patient-specific splint design?
• Moulding the inner hand with clay
• Manually measuring the hand
• Handheld photogrammetry scanning
• Magnetic Resonance Imaging (MRI)
• Computerized Tomography (CT)
A House of Quality helped us choose the handheld photogrammetry scanning against the other ideas, which would require too much patient cooperation (clay), be too expensive (MRI, CT) or be harmful (CT). Though measuring the hand would not produce a patient-specific splint, we decided it could still be a suitable process for producing cheaper, patient-informed splints.
• Moulding the inner hand with clay
• Manually measuring the hand
• Handheld photogrammetry scanning
• Magnetic Resonance Imaging (MRI)
• Computerized Tomography (CT)
A House of Quality helped us choose the handheld photogrammetry scanning against the other ideas, which would require too much patient cooperation (clay), be too expensive (MRI, CT) or be harmful (CT). Though measuring the hand would not produce a patient-specific splint, we decided it could still be a suitable process for producing cheaper, patient-informed splints.
Prototyping
The first handheld scanning approach we tried was using the
Autodesk Recap Photo app (Autodesk Inc., CA). It was available
in Android devices, cheap and non-invasive, but it was not
accurate enough [1].
The second approach required upgrading to a more expensive handheld scanner. Luckily, Trinity College Dublin provided us access to a Sense 3D Scanner (3D Systems, CA). With our first try [2], we realised we needed to spend a bit more time scanning the hand and that the scan needs to be slightly refined with the software, as evidenced by the 3D-printed sample of our scanning.
[1] Autodesk failure
[2] 3D-printed first attempt at scanning with the Sense
3D Scanner
Our original idea was to export the obtained hand model to
SolidWorks, carve out the splint from it and scale it up,
but SolidWorks did not allow to modify models generated with
external software. As an alternative, we incorporated one
of our scrapped brainstorming ideas: molding the inner hand with clay.
Step 1: Scan the hand with Sense 3D and polish hand 3D model
Step 2: 3D-print the hand and mold the grip shape from
clay
Step 3: 3D-print the grip model and attach it to the washable
cover
The second approach required upgrading to a more expensive handheld scanner. Luckily, Trinity College Dublin provided us access to a Sense 3D Scanner (3D Systems, CA). With our first try [2], we realised we needed to spend a bit more time scanning the hand and that the scan needs to be slightly refined with the software, as evidenced by the 3D-printed sample of our scanning.
Step 1: Scan the hand with Sense 3D and polish hand 3D model
Retrospective
This project allowed me face the challenges of working on a
team-based project with time and economic constraints. For
instance, we intended to explore an alternative 3D-printed
hand splint using only key hand measurements instead of the
hand model but only did superficially. At the same time, I had
the chance to tackle a real life healthcare problem and
acquire both technical and soft skills like additive
manufacturing, using a House of Quality, exchanging viewpoints
and pitching ideas to experts.
Contributions
All of us developed the idea. Gavin and I used Quality Function Deployment to guide decision-making. I was in charge of writing our process. Vincent drew early concept designs that the team came up with. Amjad 3D-modeled early prototypes. Kate sewed the washable covers. All of us created at least one final prototype (3D-scanning + 3D-printing).
Contributions
All of us developed the idea. Gavin and I used Quality Function Deployment to guide decision-making. I was in charge of writing our process. Vincent drew early concept designs that the team came up with. Amjad 3D-modeled early prototypes. Kate sewed the washable covers. All of us created at least one final prototype (3D-scanning + 3D-printing).
