We present BIOGEM, a fully biodegradable McKibben actuator with integrated sensing, made from gelatin-based composites. By tailoring the material compositions, we customize the mechanical and electrical properties of the biodegradable composites, creating an integrated biodegradable system that combines both actuation and sensing functionalities. BIOGEM integrates a McKibben actuating structure by using stiff gelatin as outer braiding and the stretchable gelatin as air chambers. It also integrates resistive strain sensing through ionic gelatin, allowing the actuator to monitor its own deformation without relying on conventional electronics. We characterize the actuator’s performance across key parameters including braid angle, wall thickness, and material stiffness, demonstrating reliable contraction and repeatable force output at low pressures. Biodegradation is validated through both enzyme-assisted and backyard soil studies, confirming the material’s sustainable end-of-life behavior under realistic conditions. We illustrate the potential of this platform through interactive, edible, and environmentally-degradable prototypes across human–computer interaction and soft robotics scenarios.

The hearing aid experience is not a one-size-fits-all situation. Rather, each hearing aid user and their environment is unique. This project aimed to customize the listening experience of hearing aid users by reconstructing daily sound scenes based on real-world data during hearing aid fine-tuning. Older adults with mild to severe hearing loss were recruited and randomly assigned to the experimental or control group. All participants were fitted and sent home with hearing aids for an initial field trial of two weeks. During this period, they were instructed to collect information on the sound scenes that they identified as most important to their communication needs, including communication intent, listening effort, and acoustic recordings of the scenes. Following the initial field trial, participants were invited back for hearing aid fine-tuning. Participants in the experimental group conducted self-directed adjustment of their hearing aid gain for the individualized sound scenes reconstructed in the lab based on the audio recordings collected during the initial field trial. In contrast, participants in the control group made adjustments in two non-individualized, generic acoustic environments. Following fine-tuning, the participants were sent out again for three weeks, before returning for final outcome assessments. These included speech recognition performance in background noise and questionnaires on the subjective benefits of the hearing aids. For my role, I conducted detailed analyses of the survey data collected during the two field trials and the final outcome questionnaire results. Additionally, I managed the equipment inventory to support the field trials. It is anticipated that the experimental group will demonstrate greater clinical outcomes based on speech recognition testing and subjective questionnaires than the control group. If this is confirmed, it would provide the first evidence for leveraging real-world data in individualized hearing aid fine-tuning.

Protein kinases have been found to regulate cellular processes such as growth and stress response. Thus, they act as excellent targets for drug treatment. The Mycobacterium tuberculosis (Mtb) genome encodes 11 serine/threonine protein kinases. Our lab has previously found that two of these kinases, PknF and PknL, show a large survival deficit when induced. They phosphorylate similarly throughout central carbon metabolism (CCM), a process known to be involved in cellular survival. To test kinase regulation of different pathways in CCM, I tested the growth of avirulent Mycobacterium tuberculosis (aMtb) strains expressing PknF or PknL using two different carbon sources: propionate and succinate. Propionate is broken down into propionyl-CoA, a toxic co-intermediate, which passes through the methylmalonyl or methylcitrate pathway to enter the citric acid cycle at succinate. The methylmalonyl pathway requires vitamin B12 to proceed and prevent toxic propionyl-CoA build up. Thus, propionate + B12 was tested to further elucidate regulation of these pathways. I measured colony-forming units (CFU) to quantify aMtb survival in these growth conditions. I compared survival measurements of the PknF and PknL induced strains relative to an empty vector control strain. I found that PknF induced grown with propionate showed a greater survival deficit by day 7 compared to the strain grown in succinate. Interestingly, the addition of B12 did not rescue growth as it did in the empty vector control. PknL induced grown with propionate shows a greater survival deficit compared to succinate; however, the addition of B12 decreased the survival deficit experienced in propionate. Due to this difference between B12 phenotypes, we hypothesize that PknF induction is regulating the methylmalonyl pathway, resulting in no rescue of the survival deficit. These findings can be used to inform future studies on PknF and PknL as potential targets for tuberculosis treatment during infection.

Chlorpyrifos (CPF) is a widely used organophosphate pesticide effective in controlling agricultural pests by inhibiting acetylcholinesterase, leading to the accumulation of acetylcholine and continuous nerve stimulation. CPF exposure has been linked to increasing autism risk and gut microbiome dysbiosis. However, the underlying mechanism linking CPF to autism remains unclear, and the role of the gut microbiome in CPF-induced neurodevelopmental toxicity remains elusive. Using a high-throughput social behavior assay, we found that embryonic exposure to CPF caused lasting social deficits in zebrafish. We then screened seven common gut microbiome metabolites and found that butyrate effectively rescued CPF-induced social deficits. Butyrate is a known inhibitor of histone deacetylases (HDACs). We discovered that valproic acid, an inhibitor of Class I and IIa HDACs, phenocopied butyrate’s rescue effects. Meanwhile, trichostatin A, an inhibitor of Class I, II, and IV HDACs, and nicotinamide, an inhibitor of Class III HDACs, did not. We are currently conducting multi-omics analyses; including metagenomics, metabolomics, RNA sequencing, and CUT & RUN, to further elucidate the mechanisms underlying CPF’s neurodevelopmental toxicity and butyrate's rescue effects. In the long run, our work will help to uncover how CPF exposure contributes to autism risk and to inspire new therapeutic approaches for alleviating autism-related social deficits.

The ability to recognize that others have mental states, separate from us, and that these states are not always accurate portrayals of reality, is central for theory of mind (TOM). This capacity becomes particularly crucial when children explain causal relationships, as they must integrate their understanding of causality with their awareness of other's knowledge states. Skills like this are essential for effective communication and reflect a key developmental milestone in both cognitive and social reasoning. This study examines how children process causal scenarios while considering and tracking the knowledge states of multiple people. We will examine how children (ages 4-7) perform with conjunctive causal relationships, where two separate effects must combine to produce an outcome (e.g., watering a plant and giving it fertilizer causes it to bloom). Children are asked to explain how the outcome happened, and what knowledge each character has. The children will be given four causal events, varying in content, and follow the same causal structure, where each character is only aware of one cause (A or B). After the scenario, children will answer open-ended questions to assess their recall of what each character knows and test their understanding of how the outcome (C) occurred. We predict that younger children will recognize the causal outcome but struggle to differentiate knowledge states, while older children will demonstrate an improved ability to tailor their explanations based on other's perspectives. This study extends beyond previous studies that primarily focused on children's passive evaluation of explanation as our study will investigate children's active role in generating explanations tailored to different character's knowledge states. Our findings will contribute to the understanding of how the development of TOM shapes children's ability to understand and reason about causal relationships.

The proximal tubule (PT) and glomerulus are vital blood-filtering components of the nephron, the functional unit of the kidney. The components’ micro-scale sizes and intricate three-dimensional structures are critical to kidney function, although accurate in vitro modeling has proven difficult. Limitations in fabrication techniques have forced size scaling and imprecise morphology in models. In this study, we addressed fabrication limitations using multiphoton ablation to etch intricate, three-dimensional proximal tubule and glomerulus vessels in collagen hydrogels. We sought to demonstrate model viability by introducing human proximal tubular epithelial cells (hPTECs) and human umbilical vein endothelial cells (HUVECs), respectively, through cell perfusion. However, we encountered a significant challenge: due to the small diameter and high curvature of the micro-scale channels, the cells tended to aggregate, disrupting cell profusion and cellularization throughout the vessels. Cell aggregation was especially prominent in the glomerulus model due to the more tortuous and complex geometry. While our cellularization trials on native-scale models proved it is feasible to perfuse cells throughout the vessel, we still need to refine cellular profusion and cellularization. To improve cellular profusion and cellularization, we are first studying a 1.5-scale glomerulus model. The scaled model's increased vessel diameter and lower curvature demote cell aggregation and enhance the ease of cell profusion. We anticipate that cellularizing the 1.5-scale model will provide a deeper understanding of the variables facilitating cell profusion that we can use to improve native-scale vessel cellularization. Fabricating native-scale, accurate in vitro PT and glomerulus models is crucial for developing a deeper understanding of hemodynamic influence on kidney function. These findings contribute to the fabrication of more biomimetic in vitro PT and glomerulus models that will pioneer therapeutics and the understanding of kidney physiology and pathology.

Privilege and oppression affect many aspects of Asian Americans’ lives. Most notably, Asian Americans are constantly surrounded by discussions that perpetuate harmful messages that lead to discrimination based on their race and gender. Yet based on past research, Asian Americans are caught in a unique position in terms of defining their racial privilege and viewing their societal advantages and disadvantages compared to other racial minorities (Oh & Eguchi, 2022). Additionally, Asian media like K-pop may play a role in giving Asian Americans a chance to embrace their culture and, possibly for Asian American men, give them a chance to push away the many oppressive stereotypes that surround their identities. For our research, we investigated how privilege is felt throughout the Asian American community, how ethnicity and gender play a role in Asian Americans’ sense of privilege, and how Asian media impacts their definitions of privilege. Using a grounded theory approach, we analyzed qualitative data from Asian American college students at UW Bothell. Semi-structured interviews were conducted with five participants so far, and we anticipate collecting data from at least five more participants by the time of the presentation. From our interviews, we have found that the perception and experiences regarding racial privilege vary among different ethnicities among Asian Americans (e.g., East vs. South vs. Southeast Asian groups). Additionally, we have found that struggles in the dating scene shaped Asian American men’s views of lacking privilege. Finally, many interviewees felt that Asian media, particularly K-pop and anime, play a key role in shaping how they view themselves as privileged and increasingly value their Asian American identity. Our study points to the need for future scholarship on the analysis of Asian media’s role within Asian Americans and the different types of privileges felt between different ethnicities and genders.

Pulmonary Arterial Hypertension (PAH) is a deadly vascular disease, affecting the blood vessels of the lungs, with no existing cure. PAH is characterized by pulmonary arterial smooth muscle cell (PASMC) hypertrophy and hyperplasia, which increases resistance to blood flow within the pulmonary arteries, leading to rapid symptom progression and eventual death from right heart failure. My mentor and I hypothesize that defects in PASMC differentiation and alignment may contribute to PAH. To test whether alignment and phenotypic responses differ in patients with PAH, we designed a micropatterned collagen scaffold atop a glass coverslip. Explanted PASMCs from patients with PAH or failed donors (controls) were cultured on alternating 10-µm wide x 10-µm deep microchannels or unpatterned constructs and alignment, protein expression, and cellular morphology were compared across conditions. I evaluated 3 PAH and 3 control subjects and have collected preliminary data for each condition (control versus PAH), with three technical replicates each. Through these preliminary studies, I have demonstrated success of my model with consistent alignment observed on patterned substrates. Excitingly, PASMCs from patients with PAH expressed significantly decreased levels of the contractile protein, Calponin, when compared with control cells, including after responding to cues that promote alignment and contractility. This suggests that PAH PASMCs remain in an inappropriately synthetic or proliferative state. Moving forward, I plan to evaluate additional micropatterns by varying dimensions of rectangular and sine waves designs using an ablation protocol with a 2-photon microscope laser. Subsequent evaluation will include immunofluorescent staining of contractile and other SMC markers as well as transcriptomic evaluation of cellular responses to micropatterning. This work will enhance understanding of whether SMC abnormalities contribute to disease initiation and progression in PAH and will contribute to the broader effort of developing more complex models of pulmonary vascular disease.

Traumatic brain injury (TBI) is one of the leading causes of death in young adults. It is initiated by loss of endothelial junctions during deterioration of the blood-brain-barrier. Investigation into endothelial barriers has been enabled by high-resolution imaging via confocal microscopy. However, existing image analysis tools struggle to capture the complexity of EC morphology due to their reliance on rigid segmentation, limiting their ability to extract meaningful insights. My project focuses on developing a more effective method for analyzing ECs by implementing a pixel-based computational tool that provides a more nuanced analysis of EC junction integrity and morphology beyond traditional segmentation methods. Immunofluorescence (IF) images were obtained from an in vitro model of TBI mimicking 3D brain microvessels which were treated with kinase inhibitors (KIs) to determine which kinases promote or hinder recovery. If ECs remained damaged after treatment, it indicate the inhibited kinase was essential for recovery. If they improved, the kinase was likely disruptive. To identify these effects of KIs on EC based on IF images, I developed a pixel-based clustering tool that analyzes junction intensity without forcing explicit segmentation. By analyzing pixel intensities relative to cell nuclei, I generated profiles of each vessel that represent the tightness of EC junction. I used an existing AI-based tool, Cellpose, to define nucleus masks and wrote a customizable Python script to compute pixel distances and intensity variations, providing a detailed, unbiased view of EC behavior. Preliminary findings suggest that this method enhances the accuracy and efficiency of cellular analysis by eliminating segmentation bias and capturing subtle morphological changes. Future work involves integrating this tool with regression models to identify kinases that regulate EC junction integrity. This research has broad applications in vascular disease modeling and drug discovery, offering a new approach for studying cell behavior and developing targeted therapies. 

Children are not merely passive observers; they actively seek to understand the why behind events. A fundamental distinction in causal reasoning is between agentic causes, which attribute outcomes to the actions of an agent like a person, and non-agentic causes, which focus on environmental factors. Do children show preferences for agentic versus non-agentic explanations? Moreover, are they influenced by the outcome’s valence (positive or negative)? This study examines how outcome valence influences children's (4-9 years old) preferences for agentic versus non-agentic causes in situations where the cause is ambiguous. By analyzing their explanatory preferences, we investigate how the valence of outcomes shapes causal reasoning across development. Participants will be presented with scenarios describing everyday events. Each scenario will have a clear positive or negative outcome, and the cause of the event will be ambiguous, with both agentic and non-agentic explanations being plausible. For example, some participants might see an apple falling perfectly into someone's hand (positive), while others see it hitting their head (negative) - events that could be attributed to either a squirrel jumping up and down, or the wind blowing. Participants will then be asked to answer what caused the outcome via a forced-choice task. We predict that children will more often select agentic over non-agentic causes for negative outcomes compared to positive ones. We also expect that as age increases, their choice differences based on outcome valence will be more pronounced. This investigation helps us understand whether agency itself plays a role in early causal reasoning. If children demonstrate a stronger preference for agentic causes in negative outcomes, this may suggest that emotional valence influences how children construct causal explanations. Furthermore, examining children’s explanatory preferences - whether biased toward agentic causes or not - can tell us how they incorporate agency into their developing understanding of causality.

This research focuses on improving speech understanding for individuals with hearing loss caused by a gene mutation affecting the stereocilin protein (STRC). The STRC mutation, which impacts the outer hair cells in the cochlea, is the second most common genetic cause of inherited hearing loss, affecting approximately 14.36% of individuals with mild to moderate hearing loss. Although this mutation doesn’t cause profound deafness, it significantly impairs the ability to distinguish speech, especially in noisy environments. The project proposes the use of spectral contrast enhancement (SCE), a signal processing algorithm that sharpens the auditory spectrum to improve speech clarity. Previous studies have shown that the SCE algorithm benefits cochlear implant users with poor spectral resolution, and this research adapts the algorithm specifically for those with STRC-related hearing loss. By enhancing spectral content, the algorithm helps make speech more intelligible in complex listening situations, such as background noise. I am conducting a behavioral evaluation with normal-hearing participants, simulating STRC-related hearing loss via the online platform Gorilla. The experiment measures hearing thresholds, word recognition with and without the SCE algorithm, and speech clarity ratings to assess the algorithm's efficacy. With the help of Dr. Yi Shen, I designed the experiment and created the user interface for the test. The current step involves adding more words into the SCE test for comparison with and without the algorithm, allowing for a comprehensive evaluation of the algorithm's impact on speech recognition and clarity. This work represents a significant step forward in audiology by applying precision medicine to hearing loss treatment. It aims to provide a tailored, evidence-based solution for individuals with STRC mutations, improving their ability to communicate in everyday settings and enhancing their overall quality of life.

Intrinsic hand muscles and tendons are crucial for joint stabilization, fine motor control, and coordinating flexion—functions essential for performing dexterous tasks such as typing, grasping, and tool manipulation. However, monitoring strength and real-time activities remains challenging. Surface electromyography (EMG) struggles to isolate signals from interior tissue due to low signal-to-noise ratios. Devices like the Rotterdam Intrinsic Hand Myometer measure strength but are cumbersome for continuous monitoring. Electrical Impedance sensing offers a promising alternative. This technique passes a low-frequency electrical current through electrode pairs (injectors and receivers) on the skin and measures the resulting voltage changes to model tissue impedance. Through this approach, we can track and classify the activity of hand muscles and tendons in real-time, targeting the challenge of capturing signals within the hand. Our approach integrates a custom conductive fabric electrode array into a wearable form, such as a glove or a flexible bandage, to detect impedance variation with muscle contractions. These signals are processed through a regression-based machine-learning algorithm that predicts hand poses. A dynamic simulation further visualizes the motion and corresponding muscle activity, providing feedback on intrinsic muscle coordination. By offering real-time monitoring of deeper musculoskeletal dynamics, our system opens new avenues for analyzing muscle function and optimizing performance. Beyond research, this system can inform a range of applications—from enhancing human-computer interaction and prosthetic control to supporting personalized rehabilitation protocols. Looking ahead, we plan to optimize electrode designs for improved comfort and precision and to incorporate advanced machine-learning techniques for enhanced pose prediction. Through refinements, we aim to make EIS-based hand muscle monitoring a versatile tool for researchers, clinicians, and innovators across diverse fields.

Aberrant protein levels can lead to pathological states and subsequent disease, traditionally requiring treatment by therapeutics that work by occupying a pocket on a target protein and result in inhibition of the protein's enzymatic function. However, many high-value therapeutic targets do not have enzymatic activity and thus are not amenable to small molecule inhibition. To address this shortcoming and expand the number of druggable proteins, an intense focus on directly altering protein levels within cells has recently emerged. Targeted protein degradation (TPD) or stabilization (TPS) aims to develop therapeutics for previously undruggable targets by leveraging the endogenous protein degradation system within cells, recruiting an effector protein, either an E3 ubiquitin ligase (for TPD) or a deubiquitinase (for TPS), in proximity to a target protein. My research in the Shendure Lab  combines computational de novo protein design and high-throughput screening with the goal of identifying designed proteins capable of mediating TPD and TPS in cells. Specifically, we are collaborating with the UW Institute for Protein Design to design degrader/stabilizer binding proteins to be screened in HEK293 cells. By labeling each designed protein with a unique RNA barcode, we can leverage massively parallel DNA sequencing to characterize 6,000 de novo designed degraders/stabilizers in a single experiment. If successful, this will be the first demonstration of designed proteins that can modulate cellular protein levels, paving the way for a new therapeutic modality.

Engineered heart tissues (EHTs) have emerged as a promising tool for cardiac disease modeling and drug screening, allowing for better study of heart diseases (HDs). However, most current EHTs are composed of only a mixture of an extracellular matrix, heart muscle cells, called cardiomyocytes (CMs) and cardiac fibroblasts, without a vascular element. This prevents the study of the impacts of flow and the endothelium on cardiac function, despite their important role in both development and disease progression. Endothelial cell (EC) function is essential for maintaining cardiac homeostasis through protective signaling interactions between ECs and CMs. Disruption of endothelial function through vascular stressors such as hemodynamic changes and acute inflammation can trigger EC dysfunction, dysregulating cardioprotective signaling. It is important to incorporate the endothelial and perfusion components in EHT in vitro for better disease modeling and drug testing. The Zheng lab has developed a tube-like perfusable collagen-based EHT model, where CMs are embedded in the bulk collagen matrix, and the inner lumen of the tube can be endothelialized, serving as an effective, in vitro, model of cardiac vasculature. This project controls the size of the inner tube diameter of this model utilizing structural and contractile properties of muscle cells. Through the integration of these cells, we can maintain the inner diameter under a range of flow conditions, and subsequently use the model to identify healthy and unhealthy flow conditions within the EHTs. This project establishes a perfusable EHT model that allows us to examine EC function under several flow-related changes and, in the future, assess the effect of endothelial dysfunction on cardiac function.

A factor influencing the ability to tune into a single speaker in the presence of competing speech is speech rhythm. The Selective Entrainment Hypothesis suggests that attention fluctuates periodically and synchronizes with speech, a quasi-periodic stimulus. This synchronization allows the brain to predict when the most salient parts of speech will occur and direct attention towards those moments. According to the hypothesis, more rhythmic speech should be easier to synchronize with, as it is more predictable. This hypothesis has been supported by previous behavioral research, which found that altering the rhythm in the target speech stream decreased comprehension of the target speech, while rhythm distortion in the background improved comprehension, likely because it became a weaker competitor. The present study replicated and extended these findings by recording electroencephalographic (EEG) data from listeners (N = 20) to measure phase locking, or synchronization, between the target speech envelope and neural activities. I ran EEG sessions, which began by exposing participants to the target speaker’s voice on its own. Participants then listened to 300 sentence pairs, which I created by playing a sentence spoken by the background speaker and sentence from the target speaker simultaneously. The sentence pairs were divided into three rhythm alteration conditions: target-altered, background-altered, and neither-altered. After each trial the participants answered a multiple choice comprehension question to collect behavioral data. Using EEG allowed for a more direct measurement of synchronization compared to behavioral results alone. We test the hypothesis that in the conditions there will be the strongest phase locking in the background-altered condition, followed by the neither-altered, and worst in the target-altered condition, a pattern that mirrors the behavioral results. This will provide more insight into the role of rhythm in speech processing and has potential future implications for hearing aid development. 

Perfectionism is defined as “striving for flawlessness and setting exceedingly high standards for performance, accompanied by tendencies for overly critical evaluations” (Stoeber, 2011). It has become a growing topic in mental health research, particularly in understanding its impact on well-being for people of color. Among Asian Americans, cultural expectations, the “model minority” stereotype, and discrimination have been linked to increased depressive symptoms and perfectionistic tendencies (Suh et al., 2023). Given these high stakes, our research aims to understand how racial, ethnic, and cultural identities influence the views and experiences of perfectionism and self-compassion among Asian Americans. Using a grounded theory approach (Charmaz, 2006), we analyzed qualitative data from Asian American students at the University of Washington Bothell. We have conducted semi-structured interviews with five participants so far and anticipate collecting data from at least five more participants by the time of the presentation. Our findings reveal that Asian American participants often struggled with perfectionism in the past, largely driven by pressure from their immigrant families and the academic expectations of the model minority stereotype. Shaped by these experiences, perfectionism influenced their daily lives. Whether it was pressure to game efficiently, maintain high grades, or follow strict, regulated gym and eating routines, participants described perfectionism as wanting to optimize every aspect of their lives. However, many found healing through forgiving themselves, which we connected to a form of self-compassion. We aim to use this knowledge to help students develop stronger self-compassion techniques, ultimately improving their well-being and quality of life. Our study findings point to the need for future scholarship and practice on culturally sensitive counseling approaches that acknowledge how perfectionism can be shaped by cultural identity and other intersecting factors, allowing for more effective support and intervention.

The auditory brainstem response (ABR) tests are used to objectively evaluate the clinical hearing threshold of infants and young patients. However, the ABR testing process can be time and resource-consuming, as audiologists have to test multiple frequencies. For each frequency, an ABR threshold (the lowest level at which a discernable ABR response is detected) must be determined by repeating the test for a multitude of levels. The efficiency of these tests depends on clinical expertise. Audiologists can expedite this process by utilizing their experience to quickly analyze the ABR waveform and jump to the next test, skipping redundant intermediary steps. Clinicians with this expertise might not be widely available. To address this issue, the long-term goal of this study is to create an automated system that can mimic the efficient testing procedure of experienced audiologists using machine learning. A set of clinical ABR data was leveraged for model development. Our baseline models operate by analyzing one waveform at a time and predicting the next stimulus a clinician would choose based on individual waveforms. We hypothesize that a neural network that treats ABR waveforms collected in a single session as a time series would outperform baseline models. We are comparing these baseline models with neural networks that hold memory, meaning they treat ABR waveforms collected in a single session as a sequence. Multiple models were built and evaluated, including multiple time series neural networks (e.g., Long-Short Term Memory model). Initial testing indicates that including sequential data ordered as time series results in better performance. The outcome of this research is likely to improve the efficiency of ABR testing without requiring real-time supervision of expert clinicians.

Physical rehabilitation sensing technologies play a critical role in enhancing patients’ recovery through real-time monitoring and help doctors evaluate the effectiveness of rehabilitation treatment. However, traditional sensing devices are bulky which may not only limit the patients’ movement and reduce the accuracy of doctors’ evaluation but also add additional burden to the patients. Thus, we want to develop a unified multimodal sensing wearable, capturing multimodal data in a more compact and efficient form factor, allowing the patients to perform rehab tasks in a more natural way. While a multimodal wearables strategy does exist, their sensors usually stack on top of each other for multimodality, which sacrifices flexibility, and compactness, making patients inconvenient to wear. To address these limitations, we developed a novel multifunctional smart oversleeve, integrating a customized portable sensing circuit that can perform joint deformation monitoring and measure muscle activities through electrical impedance tomography (EIT) and electromyography (EMG). The sensors of the circuits are highly unified as well as the readout circuit. Compared with traditional bulky sensors with multiple layers, patients can easily wear them as regular sleeves, which combines the function of reading all of the signals that are mentioned above (EMG, EIT, etc.). From the perspective of the circuit, it can effectively calculate the bending angles of the elbow and track the activities of the bicep, triceps, and forearm muscles, reflecting the patients’ recovery performance. These capabilities provide valuable insights into patient recovery performance and highlight the potential of this device as a versatile tool for physical rehabilitation monitoring.