Bio

I'm a Cardiothoracic Surgery resident at Stanford Health Care. I also completed an intern year in Pediatrics resident at Boston Children’s Hospital before transitioning to cardiothoracic surgery. I received my MD from Harvard Medical School in the Health Sciences and Technology program joint with MIT. I trained as a biomedical engineering at the Johns Hopkins University with a focus in instrumentation.
I've interests in medical devices spanning from assistive robotics, surgical devices, to point of care devices. I have extensive experience working in the electronics and coding aspect of device development.

My long term goal is to become a congenital cardiovascular surgeon and improve the field of transplantation (partial and whole), congenital cardiac surgery techniques, and congenital mechanical circulatory support. This vocation comes from my personal experience receiving a heart transplant in 1999.

Clinical Focus

  • Cardiothoracic Surgery
  • Residency

Professional Education

  • B.S., Johns Hopkins University, Biomedical Engineering, Instrumentation (2017)
  • M.D., Harvard Medical School, MIT: Health Sciences and Technology Program (2022)

Contact

Current Clinical Interests

  • Congenital Cardiac Surgery
  • Cardiothoracic Surgery
  • Transplantation
  • Mechanical Circulatory Support Devices

I am currently a resident in Stanford's integrated cardiothoracic surgery residency. As a child heart transplant recipient, I am passionate about the pediatric cardiac population. I aim to help children with cardiac illness return to normalcy and live a fulfilled life pursuing their dreams. I plan to do this through training in pediatric cardiac surgery after this residency, and research in the field, including partial heart transplantation, surgical techniques, mechanical circulatory support devices, and transplantation immunology (tolerance induction, optimized immunosuppression regimen, rejection monitoring techniques, and understanding immunology).

All Publications

  • A Pediatric Knee Exoskeleton With Real-Time Adaptive Control for Overground Walking in Ambulatory Individuals With Cerebral Palsy FRONTIERS IN ROBOTICS AND AI Chen, J., Hochstein, J., Kim, C., Tucker, L., Hammel, L. E., Damiano, D. L., Bulea, T. C. 2021; 8: 702137

    Abstract

    Gait training via a wearable device in children with cerebral palsy (CP) offers the potential to increase therapy dosage and intensity compared to current approaches. Here, we report the design and characterization of a pediatric knee exoskeleton (P.REX) with a microcontroller based multi-layered closed loop control system to provide individualized control capability. Exoskeleton performance was evaluated through benchtop and human subject testing. Step response tests show the averaged 90% rise was 26 ± 0.2 ms for 5 Nm, 22 ± 0.2 ms for 10 Nm, 32 ± 0.4 ms for 15 Nm. Torque bandwidth of P.REX was 12 Hz and output impedance was less than 1.8 Nm with control on (Zero mode). Three different control strategies can be deployed to apply assistance to knee extension: state-based assistance, impedance-based trajectory tracking, and real-time adaptive control. One participant with typical development (TD) and one participant with crouch gait from CP were recruited to evaluate P.REX in overground walking tests. Data from the participant with TD were used to validate control system performance. Kinematic and kinetic data were collected by motion capture and compared to exoskeleton on-board sensors to evaluate control system performance with results demonstrating that the control system functioned as intended. The data from the participant with CP are part of a larger ongoing study. Results for this participant compare walking with P.REX in two control modes: a state-based approach that provided constant knee extension assistance during early stance, mid-stance and late swing (Est+Mst+Lsw mode) and an Adaptive mode providing knee extension assistance proportional to estimated knee moment during stance. Both were well tolerated and significantly improved knee extension compared to walking without extension assistance (Zero mode). There was less reduction in gait speed during use of the adaptive controller, suggesting that it may be more intuitive than state-based constant assistance for this individual. Future work will investigate the effects of exoskeleton assistance during overground gait training in children with neurological disorders and will aim to identify the optimal individualized control strategy for exoskeleton prescription.

    View details for DOI 10.3389/frobt.2021.702137

    View details for Web of Science ID 000668906200001

    View details for PubMedID 34222356

    View details for PubMedCentralID PMC8249803

  • An organosynthetic soft robotic respiratory simulator APL BIOENGINEERING Horvath, M. A., Hu, L., Mueller, T., Hochstein, J., Rosalia, L., Hibbert, K. A., Hardin, C. C., Roche, E. T. 2020; 4 (2): 026108

    Abstract

    In this work, we describe a benchtop model that recreates the motion and function of the diaphragm using a combination of advanced robotic and organic tissue. First, we build a high-fidelity anthropomorphic model of the diaphragm using thermoplastic and elastomeric material based on clinical imaging data. We then attach pneumatic artificial muscles to this elastomeric diaphragm, pre-programmed to move in a clinically relevant manner when pressurized. By inserting this diaphragm as the divider between two chambers in a benchtop model-one representing the thorax and the other the abdomen-and subsequently activating the diaphragm, we can recreate the pressure changes that cause lungs to inflate and deflate during regular breathing. Insertion of organic lungs in the thoracic cavity demonstrates this inflation and deflation in response to the pressures generated by our robotic diaphragm. By tailoring the input pressures and timing, we can represent different breathing motions and disease states. We instrument the model with multiple sensors to measure pressures, volumes, and flows and display these data in real-time, allowing the user to vary inputs such as the breathing rate and compliance of various components, and so they can observe and measure the downstream effect of changing these parameters. In this way, the model elucidates fundamental physiological concepts and can demonstrate pathology and the interplay of components of the respiratory system. This model will serve as an innovative and effective pedagogical tool for educating students on respiratory physiology and pathology in a user-controlled, interactive manner. It will also serve as an anatomically and physiologically accurate testbed for devices or pleural sealants that reside in the thoracic cavity, representing a vast improvement over existing models and ultimately reducing the requirement for testing these technologies in animal models. Finally, it will act as an impactful visualization tool for educating and engaging the broader community.

    View details for DOI 10.1063/1.5140760

    View details for Web of Science ID 000540971700001

    View details for PubMedID 32566890

    View details for PubMedCentralID PMC7286700

  • Design Advancements toward a Wearable Pediatric Robotic Knee Exoskeleton for Overground Gait Rehabilitation Chen, J., Hochstein, J., Kim, C., Damiano, D., Bulea, T., IEEE IEEE. 2018: 37-42

    View details for Web of Science ID 000852956200007