PRE2017 3 Groep7
In the U.S., it is estimated that one in every 190 people have suffered from limb loss.. This shows the importance and opportunity of prosthetics. For all these people, part of their old functions can be regained with the use of a prosthetic limb. While technology evolves, the prosthetics are able to perform more functions and are easier to handle. Where old prosthetics are mostly body-powered, they are now myoelectric or even robotic. These robotic prosthetics should eventually be able to mimic all old functions of the lost limb.
One of the challenges in the field is the hand. Especially the wrist is difficult. This joint creates a lot of movement, working with the forearm. To make a joint with as much movement as the wrist and the same power, has proven to be a difficult task. How can one design a full flexible wrist, while also giving it enough strength to lift objects? That will be one of the main questions during this project.
Another big challenge is how to control the prosthetic. Some of the newer, robotic limbs can actually work with the nerve system or the brain. This still proves difficult, since the user will need to learn to use the prosthetic in a natural way and some limbs, like the arm, have many different degrees of freedom to take into account. However, machine learning might prove a way for the prosthetic and the user to meet halfway: the user has to adjust to the prosthetic, and the prosthetic will learn how the user behaves. How do these algorithms work and what could it mean for the industry? By making our own algorithm, we will try to find out whether this might be a breakthrough for prosthetic use.
USE: It is important to look at the user aspects of wrist prostheses. For this there will be looked at the end users, society and enterprise.
Users: The users of a hand prothesis will be people who have somehow lost their hand or arm entirely. Their current way of living would be improved by giving them the possibility to use their prosthesis to pick up objects, which would also help them with basic uses of the hand. Further development could lead to even more possibilities such as catching objects or typing. This would greatly improve the quality of life for these people.
The preferences of the users would of course be a full-fuctioning arm and hand with perhaps even additional functions. The question is whether or not this is desirable, since if a prosthetic hand is more useful than u human one it could incentivise people to have a prostetic hand even if their current hand is still functioning.
Society: A hand prothesis will allow people who lose their arm or hand to more easily rehabilitate to their normal lives and jobs.
Enterprise: The enterprise will be able to sell prostheses.
The results of this project will be presented in the form of a 3D Functional Model (FuMo) together with an algorithm. The model will consist of a design for a prosthetic hand and wrist in a 3D environment (Probably NX10). Since the design will be virtual as of now, the two deliverables cannot be combined to give a single result. However the algorithm's functionality will still be proven in another way. If in the next couple weeks it is concluded that a physical model is possible to make within the given time frame, the option will be considered.
|Name||Week 1||Week 2||Week 3||Week 4|
|Eva||Search for useful sources and make a planning; do research on robot hands||Relate research on human hands to the research on robotic hands; start on the design (FuMo)||Work on the design||Finish draft|
|Jurre||Finding sources; do research on human hands||Relate research on human hands to the research on robotic hands||Aid in either the design or software||Finish draft/first algorithm; wiki up-to-date|
|Karsten||Write about deliverables; do research on control mechanism for prosthetic hand||Start on the design (FuMo)||Work on the design; implement stability/force feedback||Finish draft|
|Steven||Write about users; do research on machine learning for prostheses||Start on machine learning algorithm||Work on machine learning algorithm||Finish first version of algorithm|
|Thijs||Do research on machine learning for prostheses||Start on machine learning algorithm||Work on machine learning algorithm||Finish first version of algorithm|
|Name||Week 5||Week 6||Week 7||Week 8|
|Eva||Improve design||Finish design; work on presentation||Presentation||-|
|Jurre||Aid in either the design or software||Finish project; work on presentation||Presentation||-|
|Karsten||Improve design||Finish design; work on presentation||Presentation||-|
|Steven||Improvements in efficiency/running time of algorithm||Finish algorithm; work on presentation||Presentation||-|
|Thijs||Improvements in efficiency/running time of algorithm||Finish algorithm; work on presentation||Presentation||-|
The yellow fields are the milestones.
State of the art
The human hand
The human hand can be separated into three main parts. The forearm, the wrist and the fingers. For clarity we will look at each part separately. The fingers consist of two hinge joints and condyloid joint at the base of the digit. While they are separate joints, they cannot work independently. A tendon connects each digit with the associated muscles in the forearm. For each digit there is a pair of muscles of which one extends and one curls the digit. There is a second group of muscles also situated in the forearm that spreads the fingers apart. 
The thumb is the only digit that slightly differs from this. By allowing one more degree of freedom to the first joint and adding a muscle in the hand that allows movement in this direction.
The wrist consists of several bones that together function as a single condyloid joint. This allows for it to flex, extend and deviate to both sides. The degrees of motion for the joint are 60° for flexing and extending and 20-30° deviation to both sides.  The forearm acts like a pivot joint using the two bones there to rotate the wrist. This gives the wrist about 180° of rotation. The forearm is also the place where almost all of the muscles controlling the hand are situated. This allows for the muscles to become larger and therefore stronger than if they were confined within the hand.
- ↑ K. Ziegler-Graham, E. J. MacKenzie, P.L. Epharim, T. G. Travinson, and R. Brookmeyer. Estimating the prevalence of limb loss in the united stated: 2005 to 2050. Archives of Physical Medicine and Rehabilitation, 89:422-429, March 2008.
2. C. L. Taylor, R. J. Schwarz. The anatomy and mechanics of the human hand. "Artificial limbs", 1955