Project Goal: Develop an improved design for the dated polio leg brace.

People who have poliomyelitis, a virus-induced disease that causes muscle atrophy, rely on orthotic devices such as knee braces to compensate for muscle weakness. The most common devices are passive and provide limited support to users. The team redesigned the passive knee brace by adding a mechanical system to assist users with motions such as sitting down and standing up from a chair, walking up a set of steps, and navigating inclines. The main goal behind this design is to support body weight and assist users with knee joint extension and flexion by reducing the pressure on the joint.

The new knee brace system consists of a spring housing assembly, compression springs, galvanized steel wire, a latching mechanism and a radial moment arm. The radial moment arm is connected to the spring housing through the galvanized steel wire and operates with the hinge on an existing brace. The latching mechanism houses a latch and a stopper that lock the spring, allowing the user to freely flex and extend the knee.

The new brace weighs approximately 1.3 kg, offers an assistive moment of at least 480 pounds-per-inch, can support a weight up to 180 pounds and allows a minimum of 90 degrees of flexion relative to the user's thigh.

Project Goal: Design and build a prototype of an electronic continuously variable transmission, or E-CVT, to replace the current mechanical CVT on the Baja SAE race vehicle.

The Baja race car's mechanical CVT had two major issues that served as the primary reasons for undertaking this project. The first issue was the tedious and error-prone process of tuning the CVT. The second issue was the mechanical CVT not being properly sealed, which put the components inside at risk for dirt and water damage. The team designed and built a prototype E-CVT to solve these issues for the Society of Automotive Engineers, or SAE, Baja Competition.

The E-CVT design consists of two pulleys that connect the engine and gearbox and which change their diameter based on data collected from a telemetry systemin the engine. The E-CVT uses electric motors in conjunction with sensors and microcontrollers to algorithmically change the gear ratio between the engine and gearbox. The E-CVT's insulated wiring and protective casing at IP54 certification level ensures it is protected from water and dirt in the off-road racing environment.

The new system offers greater adjustability and increased reliability. Acceptance tests showed the E-CVT system was capable of handling overvoltage and overcurrent, as well as collecting and sending data to the central data collection microcontroller. The bench test of the completed E-CVT displayed the changing gears at the engine's peak power.

Project Goal: Create a prototype of a detachable motorized assist for standard manual wheelchairs.

Motorized wheelchairs provide users a labor-free way to move up to five miles per hour, but they can prohibitively cost up to $40,000. On the other hand, users of manual wheelchairs must continuously physically exert themselves to propel forward.

The team developed Momentous, a prototype wheelchair accessory that provides a motorized assist to a standard-sized manual wheelchair. This device can be attached to the back of a manual wheelchair and has drive-wheels that control the wheelchair based on user inputs from a joystick. Momentous is meant to last longer than similar wheelchair accessory products on the market

Project Goal: Update robotic writing technology that is capable of emulating human handwriting while emphasizing efficiency, scalability and reliability.

The repetitive nature of hand-copying messages for diverse groups of recipients and addressing different envelopes is tedious. This project presents anew type of a robotic writing machine, or RWM, which produces an efficient handwriting process and prints large quantities reliably and consistently.

The team updated the RWM technology which has been used since the 1970s by developing a new plotter that controls the movement of the pen and a paper. They also created atop-feeding method to replace the outdated bottom feed. The new feeder increased the loading capability from 200 envelopes to 500 with fewer paper jams. This reduces the time required to replenish the paper. Rollers move individual cards and envelopes from the stack to the writing surface. The message or address is then printed on the card or envelope, respectively.

The upgrade provides more writing space and less movement during the print. The Raspberry Pi allows the user to remotely send work batches to the RWM in the form of a SVG file, a significant upgrade from the previous process, which involved tinkering with the robot and provided limited input options.

Project Goal: Design and fabricate a remote-controlled mechanism for the removal of grasshoppers from agricultural fields.

Arizona is home to more than 300 species of grasshoppers that feed on plants, putting crops –specifically organic crops–at risk.

Grasshoppers naturally jump in the presence of danger. The Grasshopper Harvester III is a remote-controlled kart with a directive vacuum system that captures grasshoppers as they jump. As grasshoppers land in the capture mechanism, they are directed towards an air stream powered by the vacuum system, which pushes them into a removable storage bag. This storage bag can be easily removed and replaced by the operator.

The kart utilizes remote-controlled motors to maneuver through crop fields and efficiently collects 70% of the grasshoppers it encounters.

Project Goal: Develop a benchtop demonstration system to show the feasibility of measuring volume dispensed for tissue staining systems using a capacitive sensor.

A key factor in tissue staining quality is the volume of reagent dispensed. A sensor platform that measures the volume dispensed allows the staining environment to be monitored, understood and controlled in real time throughout the staining process. This project presents a capacitive volume sensor to automate on-slide fluid volume measurements in real time.

This design uses a carefully defined sensing pattern on a printed circuit board to detect fluid on the surface of an adhered glass slide. It does so by measuring the change in capacitance of the system. A custom printed circuit and a capacitance-to-digital converter communicate with a custom graphical user interface on a host computer to report the volume sensed. Using a curve fit of experimental data, the capacitance is converted to volume and displayed as a graph on the graphical user interface.

Project Goal: Design, build and verify a system that uses light sensor data to store and calculate the volume of cancer-identifying reagents being dispensed onto a tissue sample, enabling technicians to confirm reagent volumes and avoid false diagnoses.

Roche Tissue Diagnostics’ automated tissue staining systems dispense set amounts of dye, or reagent, onto patient tissue samples to diagnose conditions such as cancer. To deliver the most precise and accurate diagnoses, the system needs to dispense the proper quantity of reagent on every sample. The team developed a new system that uses a neural network to calculate an accurate volume for each drop.

The system consists of a photoelectric sensor which is set in the path of the reagent dropper and sends a stream of analog input to a microcontroller. When a drop is detected, the microcontroller isolates the drop instance and performs preprocessing on it to prepare the analog input for the algorithm. The microcontroller then uses a pre-trained recurrent neural network to calculate an accurate volume for the drop. The volume calculation is saved with other bookkeeping data, then converted to analog and output to the Roche tissue staining system to verify the drop volume.

This system, built on advanced neural networks and made to integrate with the existing Roche Tissue Diagnostics tissue staining system, helps to verify the integrity of the tissue staining system at each drop, preventing patients from receiving false diagnoses.

Project Goal: Create a contactless liquid level sensor that can measure levels of tissue staining reagent with high accuracy, resolution and precision

The HE 600 machine automates tissue staining to diagnose diseases such as cancer. It dispenses reagents on top of tissue samples, which are fixed to microscope slides. The reagents are housed in 1-liter reservoirs, which use mechanical signal floats to determine liquid level. The floats are in direct contact with the reagents and so break down easily, putting excess strain on system pumps that need constant replacements. In addition, the floats also often get stuck or corroded, and thus do not accurately measure reagent levels.

This design uses contactless capacitive sensing to constantly measure the liquid level inside the reservoir. The system has a flexible printed circuit board (the sensor) and a small metal box containing the capacitive sensor chip and microcontroller. The entire system is adhered to the outside of the reservoir so that none of the components are in contact with the reagents.

The system provides real-time liquid volume levels via USB connection to a computer station with a graphical user interface. This design is meant to last the lifetime of the HE 600,creating a cost-effective and long-lasting volume measuring system.

Project Goal: Make the multifunctional displays, or MFDs, in a pilot's cockpit easier to read using course predictive software.

Commercial aircrafts are equipped with multifunctional displays, or MFDs, that use sensory equipment to collect the position of surrounding aircrafts and display them on a screen. The MFDs that pilots currently use are often cluttered with irrelevant aircraft information, making it difficult for the pilot to extract necessary traffic data. The team was tasked with developing machine learning algorithms to remove irrelevant traffic data, thereby improving pilots’ situational awareness.

The team developed three Predictive Aircraft Navigation, or PAN, algorithms, each of which includes a unique method for predicting aircraft flight paths: Convolutional Neural Network Long Short-Term Memory, Naive, and Encoder Decoder models.

Each of these models combine current and past flight data to predict future flight paths. The team then incorporated a comparison algorithm to rate the relevance of surrounding aircrafts according to their relation to the pilot. The results show a decluttered MFD so a pilot can extract critical information and make vital decisions in dense airspace.

Project Goal: Create a remote-controlled vertical farm to optimize hydroponic leafy green production.

Controlled environment agriculture aims to reduce inputs and increase outputs of food production to feed a rapidly increasing population. The V-Hive Greenbox is a modular and scalable vertical farming system designed to fill the volume of a shipping container. This project focuses on adding automated technology to the smallest fully functional scale to help reduce labor requirements.

The system has a metal frame of lighting boards with horticultural LEDs and growing boards with hydroponic growing channels. The boards are alternated in the frame for optimal light distribution to the plants. Their orientation is remotely adjustable in two dimensions to accommodate the light and space requirements of different plant species and growing phases, as well as harvesting and maintenance. This is accomplished using a belt and pulley rail system above the main frame, allowing the user to extend and retract boards out of the frame and to change the lateral spacing between lights and plants.

A Raspberry Pi can be accessed on-site using the mounted touch screen panel or remotely using Virtual Network Computing. The user can remotely control board movement, the nutrient pump, the air pump and lights. Data from environmental sensors and a camera feed can also be displayed and monitored from off site.