Senior Design Expo 2023

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Biomedical Engineering Apneaware Jiamiao Chen, Luyu Kang, Zhilin Luo, and Yujie Zhu Sleep apnea is a common sleep disorder characterized by gaps in inspiratory airflow during sleeping. It is one of the most common sleep disorders, affecting over 1 billion people worldwide. However, since the episodes occur during sleep, self-diagnosis can be challenging. Untreated, sleep apnea can have detrimental effects on health, leading to increased risks of multiple diseases, such as stroke and coronary heart disease. Existing techniques for diagnosing sleep apnea, such polysomnography, are expensive and frequently necessitate overnight stays in a sleep lab for the patients. Thus, there remains a need for an affordable and user-friendly device to monitor patients’ activities during sleep and detect the symptoms of sleep apnea. Inspired by pulmonary auscultation, our device employs acoustic detection of respiratory sounds. It consists of three components: a sound acquisition component resembling a mechanical stethoscope, a signal analysis system computing sleep apnea episodes, and a user-friendly interface allowing patients to monitor their sleep patterns and understand the implications. By accurately detecting sleep apnea events, Apneaware has the potential to raise awareness of sleep apnea in more people and encourage early prevention, ultimately improving the quality of life for those affected by this common sleep disorder. Euphony Therapeutics Djenebou Semega, Andoni Nolasco, Blake Turner, Imelda N. A. Adjei, and Andre Meddar Forty percent of children with Autism Spectrum Disorder and seventy-to-eighty percent of migraine patients suffer from hyperacusis, which is an increased sensitivity to sounds causing discomfort or even pain for the patient. Loudness Discomfort Level (LDL) describes the point at which a subject perceives the sound as uncomfortably loud. Ninety-five percent of patients with hyperacusis have an LDL of less than 77 dB, compared to the general population in whom the average is about 100 dB. As this is on a logarithmic scale, there is a significant sound tolerance decrease in hyperacusis patients that would barely bother most people. Current treatment for hyperacusis includes sound therapy and cognitive behavioral therapy to improve sound tolerance, but for most patients, symptom management includes wearing headphones to block out uncomfortable noises. Blocking sound is often helpful for reducing discomfort, but when uncomfortable sounds are part of one’s daily life, it can be difficult to balance the need for comfort and the need to perceive one’s auditory environment. Therefore, there is a need for a way to reduce exposure to sounds that may trigger negative effects in hyperacusis patients. Our solution is based on a Targeted Noise Cancellation system while allowing user specificity with the addition of an app. This device targets unwanted sounds, based on frequency, to attenuate loud sounds while retaining the quality of desired sounds (i.e. conversations). By pairing the device to an app, we allow the user to select which frequency of sounds they want to reduce depending on their condition. In other words, in the app, the user can choose the minimum and maximum frequency and number of stop bands that they want to have attenuated through their device. Lastly, the app permits the user to record the frequency of the sounds they encounter to store in the app as part of a catalog from which they can then select or change the sound they desire to attenuate at any time. 14
Biomedical Engineering PoseEst Alex Ying, Jesse Yebouet, Jonah Dewing, Jonathan Guo, and Yena Shin Physical therapy (PT) is an important tool for pain treatment, muscle strengthening, injury prevention, and rehabilitation. Frequently, PT is not accessible due to the high costs of sessions and transit inconvenience. When faced with these barriers, patients will sometimes rely on free online resources for instruction. However, these sources can be unreliable and leave patients susceptible to exacerbating their injuries. In order to encourage patient compliance, prevent injury, and promote progress in a user-friendly, cost-effective manner, we present PoseEst, a markerless joint tracking smartphone app. After a clinical questionnaire, certain exercises may be suggested for the user’s injury. Using a deep learning model, a phone camera will automatically record a patient’s joint positions through these exercises in 3D space. The app will track the movements of the user’s knee, ankle, hip, and spine and assess the exercise form based on clinically accepted metrics. The user is presented with this information to improve form, and the app automatically tracks recovery progress over time. If the injury does not improve with simple, form-corrected exercises, a writeup with a history of the injury and the exercises performed will be ready to print for an easy introduction to actual PT clinics. PoseEst serves as a cost-effective, accessible, at-home aid platform prior to physical therapy intervention that can also work in conjunction with physical therapists to monitor patient health and adherence. 15
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