Better instruments for orthopedic surgeons could shorten operating room times and improve surgical outcomes.

Cannulated screws only have threads at the end and can strip if the bone becomes infected or if too much torque is applied. The team designed a removal instrument that enables the surgeon to pull upward on the screw so that it engages uninfected bone and is then able to be unscrewed. The instrument’s two parts consist of a thin rod with a hook that enters the hollow screw through a hole, attaching to its bottom, and a handle that connects to the other end of the rod. The hook had to easily catch the screw’s end and fit through the screw, yet be strong enough to apply upward force without failing. The solid screw removal instrument is a unibody design consisting of a lever and a forked tip that encloses below the head of the buried screw. Pushing down on the lever raises the screw.

Orthopedic surgeons also need a more efficient method to remove infected tissue while simultaneously providing suction and irrigation. The team developed one instrument to perform all three functions by combining a curette, used for scaping tissue, with irrigation and suction systems. A unique design made the instrument easier to manufacture, and human ergonomics principles were incorporated into all the instruments to make them comfortable to use.

Kidney or renal disease, leading to chronic kidney disease (CKD) and eventual end-stage renal disease (ESRD) is on the rise in the U.S., affecting 37 million people, or 15% of adults. Kidneys regulate the body’s water and electrolyte balance and remove wastes and excess fluids to maintain homeostasis.

Patients afflicted with CKD and ESRD suffer from excess fluid retention and leg edema or swelling. Many of these patients also develop uncontrolled leg movement, known as restless leg syndrome (RLS). In dialysis, the standard therapy, a machine effectively functions as a kidney substitute, removing excess water and wastes. Despite the efficacy of dialysis, physicians are unable to determine a patient’s baseline water content, or what is termed “dry weight” vs. water excess, making it unclear how to optimally time recurrent dialysis.

The team constructed a wearable lower leg band measurement device containing a single, four-electrode impedance-edema circuit and an accelerometer. A constant voltage and current is applied to the circuit to determine corresponding resistance values. With this impedance value, edema can be extrapolated using a simple mathematical model. The accelerometer detects movements associated with the motion of RLS. The device communicates data to a connected iOS app. This app displays the impedance, edema and RLS detection data for patients and physicians to view.

In the fast-moving consumer goods industry, manufacturers are motivated to increase the agility of their supply chains. This also means packing lines and packing machinery need to work with more complex product portfolios, without creating long periods of downtime between production runs. Adaptive robot grippers offer opportunities to minimize changeover time and increase agility of the equipment. These grippers can adapt to a range of product geometries and consistencies without mechanical modification.

This adaptive design is based on machine learning image recognition software, a sonar positioning system and a mechanical gripper. In addition, the team added emulation software based on RoboDK to deal with the technical challenges of sourcing a robot arm. A single Raspberry Pi computer runs the camera and gripper system. To keep the gripper from damaging objects, force feedback comes from a single sensor at the end of one side of the gripper. A sonar system determines the position of each object and feeds that into the Raspberry Pi to inform the gripper where to grab.

The mechanical gripper demonstrates the real-world use of the system, while the emulation software provides a comprehensive view into what implementation may look like on the factory floor.

Tucson Village Farm is an education-based farm for youth with a central educational theme of nutrition and healthy living. More than 15,000 children make visits annually and are provided with healthy snacks, including popcorn, which is grown on the farm.

Although kids assist with the harvesting, dekerneling, and washing of the popcorn, they cannot clean and dry all of it. Each year at harvest time, Tucson Village Farm experiences a bottleneck, with manual processing eating up many hundreds of hours of staff and volunteer time.

The team created the Popcorn Processor with the ability to run either autonomously or by human power.

The washer, similar to a laundry machine, uses a motor to spin an inner drum where kernels are thoroughly washed and chaff is removed to an outer drum. The washer can be powered by a stationary bicycle to provide a more interactive and educational experience for school groups. The dryer, similar to a chili roaster, uses a motor that spins the drum while a fan dries the kernels. The dryer also includes a hand crank for manual operation, again to enhance the educational experience. The system can clean and dry up to 5 pounds of kernels within a few minutes.

Conventional hand washing involves touching multiple potentially contaminated surfaces. By minimizing the need to touch these surfaces, WashBot can reduce cross-contamination when handling raw meats and other foods or contaminants. In addition, the device reduces the amounts of water, soap and drying agents needed to wash hands.

The user begins by inserting their hands into the scrubbing chamber, where a sensor detects their hands and begins the pre-rinse and soaping stages, followed by a mechanical microfiber scrubbing phase. After scrubbing is complete, the user places their hands in a rinsing chamber for rinsing and drying. Multiple rinsing chambers are available to allow for either a quick rinse or a full wash, depending on the user’s needs. An LCD screen displays the current stage of the washing cycle, as well as status of water quantity and system maintenance.

Water used during the pre-rinse and final rinse cycles is recycled to minimize water usage, with dirty, fresh and recycled water stored in separate tanks.

The team used the engineering design process to select commercial off-the-shelf (COTS) components and design, develop, integrate and test the COTS items, resulting in an effective system that saves water and decontaminates effectively.

Knowing platelet-derived microparticle (PDMP) levels is important for proper treatment of patients with cardiac complications. Currently, determining a patient’s PDMP levels is a lengthy process that requires expensive lab equipment. The team designed and developed a dynamic light scattering system as a cost effective, point-of-care alternative for sizing and quantifying PDMPs in a blood sample.

The design uses a 520 nm laser that shines through the buffy coat of a patient’s blood sample. The PMDPs within the buffy coat interact with the beam to create light scatter that is captured by an avalanche photodiode. The intensity signal is read by an oscilloscope and processed by a Raspberry Pi to create a calibration curve using an autocorrelation function. These calibration curves are used to determine the size and quantify the PDMPs within the blood sample. A graphical user interface displays particle size and concentration. The Raspberry Pi saves and stores the optical analysis data for each run, and this data can be transferred to a separate device if desired. The entire system is housed in a dark, closed container that allows for sample access while ensuring a reliable environment for optical analysis.

Kidneys are vital organs involved in the balance of fluids and electrolytes in the body. Intaking too little or too much potassium can have serious consequences on a person’s health. For patients with chronic kidney disease, it is important to precisely moderate potassium intake. This project presents a portable potassium diagnostic system which can directly measure potassium content in food and fluid, as well as estimate potassium content through image recognition.

To directly measure potassium content, the system uses a probe which is placed into a food sample prepared using the system’s homogenizer. A camera system then takes photos to identify and estimate the volume of the food or fluid. A Raspberry Pi computer contains both a software package with an evolving database listing potassium content for specific substances and a graphical user interface which allows users to easily track and record daily potassium intake. The recorded measurements are available for use by health care providers.

Blood clotting and related diseases account for the majority of hospitalizations and disease-related deaths in the United States, affecting more than 35 million people each year. By measuring the stiffness of platelets, medical researchers can create and refine implantable medical devices to reduce a patient’s risk of developing these life-threatening conditions.

The CytoMech is a compact and cost-effective system to measure platelet stiffness. Platelets are suspended inside a microfluidic chip, imaged by a fluorescence-based microscope camera, and analyzed by the team’s software system. The CytoMech uses a method known as dielectrophoresis to stretch platelets by subjecting them to a nonuniform electric field while the image analysis system measures the change in platelet size. Researchers can use a user-friendly graphical user interface to control the system, view the platelet while specifying the electrical force applied to it, and display the final result to the user. The system calculates the stiffness of the platelet based on the applied force and the deformation. By averaging the results of tests with multiple platelet samples, clinicians will be better able to evaluate the safety of implantable medical devices and diagnose a patient’s risk for thrombosis.

Nearly 37 million people in the United States suffer from respiratory diseases such as asthma, chronic bronchitis and lung cancer. Physicians can’t capture all sound that occurs during doctors’ visits, so much of the nonverbal information from patient encounters is not extracted for further analysis.

The sound analysis system consists of three subsystems. A handheld device containing a digital stethoscope captures patient sounds using a Raspberry Pi Zero W, and a room audio capture system uses high-quality microphones to record the doctor-patient interaction. These two systems then transmit data to the third component: a server which analyzes and processes the recorded sound files using a Raspberry Pi4 and stores them securely within the clinic database. The system is equipped with various open-source codes using Python and MATLAB to extract and analyze sound components.

Condition-based maintenance (CBM) systems that use wireless sensors are becoming a popular and useful tool for identifying maintenance needs and preventing system failure. This project presents a vibration-based energy harvesting method to extend the IoT sensor battery life to around three to five years in a railroad operating environment.

The team developed an energy harvesting solution that captures vibrational and solar energy from the operating environment to recharge the IoT sensors in the CBM system. Piezoelectric generators capture the vibrational energy when vibrated at certain frequencies, and solar panels on the exterior of the system capture the solar energy. An onboard microcontroller monitors the incoming harvested energy and connects the source to the rest of the circuit when a certain voltage threshold is met. The battery charging circuit is equipped with a load sharing circuit, which allows power to be shared between the incoming power and battery to power the system.