An Investigation of Juvenile Muscle Activity for the Development of a Pediatric Prosthetic

Research Question

How can an expandable above the knee prosthetic informed by Biomechanical Gait Analysis, enhance the quality of life for pediatric amputees?

Explanation

An above the knee prosthetic leg is an artificial replacement for the full leg used in patients with primarily congenital limb deficiency, vascular disease or trauma. These devices offer users a greater chance of mobility and independence for a more active lifestyle. Both Bionic and Mechanical prosthesis are often informed through the use of biomechanical gait analysis as it allows engineers to create innovations that mimic the natural movement and stability of the human lower limb. Analyzing the movement of the leg through utilizing a type of biomechanical analysis (kinematic analysis) can allow the design to accurately simulate a natural walking gait. Thus allowing kids a greater quality of life.

This study aims to address the challenge of traditional prosthetic fitting while also cutting down on the costs of an innovative prosthetic. This is as the average price for prosthetics globally is $5000-$70,000 which is simply unaffordable and unreachable for the average family due to the factors such as the rising cost of living and uneven technology distribution of these prosthetic legs (“You Don’t Need Fancy Equipment to Make Good Prostheses,” 2024). By using the measurements and muscle analysis gathered from this lab to create an innovative cost effective prosthetic will allow to better the lives of thousands while conducting research which can be applied to improve a multitude of other biomedical designs.

How was the gait information collected?

The gait information was collected using the Myoware 2.0 muscle sensor ecosystem. Firstly a muscle sensor was placed onto a subject's hamstring or calf, which transmitted raw EMG data to Arduino IDE Serial Plotter with the help of a Red Board. The Arudino Serial plotter was then recording and storing this data actively on a computer, which has later transferred into an Arudino Uno R3 for the development of the prosthetic design. In order to identify which raw EMG readings were apart of which phase in the gait cycle there were three camera angles recording the subject's entire leg span. These camera angles were later put side-by-side with the EMG readings to determine the phase in the gait cycle based on research and an interview with a local physiotherapist. However, to minimize variability the experimental team choose the entire segment of each gait phase and matched in up with the average EMG readings at the moment in time. This synchronized gait approach combined with the use of averages allows for the prosthetic design to more accurately represent the entire gait phase as it effectively eliminates pressure spikes caused from exterior sources. While also condensing the muscle activation levels per stride, as the Arduino Serial Plotter uses milliseconds which was hard to fully account for. Altogether the algorithm coded into the design can respond to the user's intent in a less invasive and cost effective way compared to current prosthetics.

How was the experiment controlled?

The experimental procedure mainly controlled the position of the sensors on the leg in order to minimize background noise affecting the results. This was controlled using the placement guide for the Myoware sensor located on the official start-up guide (“MyoWare Muscle Sensor,” 2026). More information is on Table 3.

How does this design work?

This above the knee prosthetic leg is not a traditional prosthetic leg as it fuses elements of mechanical and bionic prosthetic designs. The device expands using a telescope mechanism in 2cm modular blocks which are assigned different colours. Through the use of a colour sensor our mechanism can detect the block colour and identify how much the user expanded the prosthetic leg by. Once this has been identified, the information is sent and matched by the Arduino. The Arduino synchronizes the current height of the prosthetic to the leg length of an able bodied individual. After the Arduino sends gait information to the knee servo motor such as the electromyographic profile and knee angles during the entire gait cycle. This information is then used by a servo motor to control the movement of the leg through the knee, once the system has detected applied pressure. These computerized components have an estimated cost of $75 which is in contrast to the $5000 components often used in bionic and mechanical prosthetics. Altogether to test the usability of this design, multiple simulations were used such as applied pressure to test if the design can withstand the energetic nature of kids and structural sound tests. After some redesigning, our final design can hold up to triple the weight for the 50th percentile of grade 3-5 students (target demographic) (“Calculate Your BMI,” 2019).

How does this design accommodate for other forms of movement?

Even though the experiment conducted only takes the muscle activation levels of children while walking, the experimental team made sure that this design would also be durable for other forms of movement. For example, the algorithm within this prosthetic uses a controlled system made up of windowed averages in order to shorten the delay in processing between initial contact (pressure) and loading response. This allows for the design to be able to handle faster movements, as the processing time wouldn't be a factor restricting motion. Additionally, this design has a rubberized foot design with a compression vault to provide an energy return to the user while doing multi-directional movements.

Findings of the Experiment

The findings of this experiment have provided the experimental team with tremendous data to use within the adaptable prosthetic design. The data collected revolving around the electromyographic profiles of 6 grade 3-5 students, has truly contributed to the quality of our prosthetic design through proving that lifelike movements can be replicated with a $75 system opposed to $5000 system. Therefore the prosthetic design that is informed with this data has transformed the accessibility of prosthetics. In order to protect the innovative features of this design, further details and graphs of the experiment will be visible only at the fair.

Why do the experiment results matter?

The results of this experiment prove that the current $75 computerized system is able to read and record muscle sensor data that accurately mimic the physical movement. Additionally the obtained electromyographic profiles of 6 students, proves that this method could be a good baseline test to collect more in depth gait analysis data for our colour-block system. This baseline test can be further used for developing a similar algorithm designed for running, so that a paediatric amputee can participate in a larger range without being restricted. Overall the results of this experiment demonstrate that a pediatric prosthetic design can be affordable, adjustable and functional for a wide range of children.

What is the implications for the current crutch design and future iterations?

The implications for this testing method and the development of this crutch design go beyond providing an affordable solution to low-income families. Due to the prosthetic's self adjustability in both lower and upper regions of the human leg, this solution can be ideal for all kids as most prosthetic devices aren't as customizable. Thus future iterations of this design that uses the same expanding mechanisms in a cheap manner can revolutionize the world of pediatric biomedical devices by giving families hope of a affordable and properly fitting solution.

Future Steps: How can this design be improved?

One of the ways this design can be improved in the future is through additional testing in order to match all prosthetic users with muscle activation levels that accurately represent their leg legnth. Doing this would further improve the algorithm within the prosthetic leg, as then this prosthetic design would accurately mimic the walking gait of all potential users. Another future step, is to repeat this experiment but using a higher speed on the treadmill in order to mimic the running cycle while creating a life size final design.

Thank you to everybody who has helped my partner and I in the process of creating our prosthetic design. The dedication and support you provided us truly allowed us to flourish and have a successful product. In particular, the science and design department teachers at our school helped us tremendously along the design process by providing us with materials and giving us constructive feedback. Additionally, a special thanks to the medical professionals who gave us valuable insight into how to properly design our paediatric prosthetic.

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