Bio


Clinical Neonatologist, Clinical Informaticist, > 5 years of Industry experience with primary research focus on health tech innovation, medical devices (wearable sensors, non-invasive sensing), global health (affordable, low-cost medical device development)

Clinical Focus


  • Neonatal-Perinatal Medicine
  • Clinical Informatics
  • Health Tech Innovation
  • Medical Device Validation

Administrative Appointments


  • Reviewer, Fulbright Campus Committee (2020 - Present)
  • Reviewer, Stanford MD, Pediatrics Residency and Neonatology fellowship admissions (2019 - Present)
  • Advisor, Stanford Health Innovations & Future Technologies (2018 - Present)

Honors & Awards


  • R01 (Non-invasive ventilation/perfusion with EIT), NIH (NIBIB) [Colorado State, GE Research]
  • MCHRI CE Grant 2022, Maternal and Child Health Research Institute, Stanford
  • SBIR Phase 2 (R44) Grant - Novel NG Tube, NIH (NICHD) [Gravitas/Theranova]
  • SBIR Phase 1 (R43) Grant - Non-invasive BP sensor, NIH (NICHD) [Pyrames]
  • MCHRI CE Grant 2020, Maternal and Child Health Research Institute, Stanford
  • Moskowitz Scholar, Mayo Clinic
  • Artificial Intelligence in Medicine and Equity Grant, Robert Wood Johnson Foundation & Stanford, Department of Medicine
  • Marshall Klaus Perinatal Award, American Academy of Pediatrics
  • Innovators in General Pediatrics, Packard Foundation
  • mHealth platform for Maternal/Child Health Grant, .
  • CATCH Grant, American Academy of Pediatrics
  • MIT $50/100K Entrepreneurship Competition, Winner, MIT, Cambridge

Boards, Advisory Committees, Professional Organizations


  • NSF Medical Devices Review Panel, NSF (2023 - Present)
  • NIH SBIB Review Panel, NIH (2021 - Present)

Professional Education


  • Board Certification: American Board of Pediatrics, Neonatal-Perinatal Medicine (2020)
  • Board Certification, American Board of Pediatrics, Pediatrics
  • Board Certification, American Board of Preventive Medicine, Clinical Informatics
  • Fellowship, Stanford University, Healthcare Design
  • Fellowship, Stanford University School of Medicine, Palo Alto, CA, Neonatology (2018)
  • Fellowship, Harvard Medical School - Massachusetts General Hospital, Boston, MA, Biomedical Informatics
  • Residency, Columbia University Medical Center, New York, NY, Pediatrics
  • MS, Massachusetts Institute of Technology, Biological Engg/Toxicology
  • MBBS, Kasturba Medical College, India, Medicine, Surgery

Community and International Work


  • India NeoDesign Network

    Topic

    Maternal and Child Health

    Location

    International

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

Patents


  • "United States Patent 8999242 Method and apparatus for monitoring alteration of flow characteristics in a liquid sample", Apr 7, 2015
  • "United States Patent US20100000862A1 Integrated Blood Glucose Measurement Device", Apr 30, 2014
  • "United States Patent US20100249965A1 Integrated Blood Glucose Measurement Device", May 1, 2009
  • "United States Patent US20100000862A1 Integrated Blood Glucose Measurement Device", Jul 7, 2008

Current Research and Scholarly Interests


Wearable senors, unobtrusive vital sign monitoring, natural language processing/text mining

Projects


  • Non-invasive continuous BP monitoring using wearable sensors, Lucile Packard Children's Hospital

    Location

    Stanford, CA

    Collaborators

    • Xina Quan, CT, PyrAmes Health
  • NICU of the Future (unobtrusive neonatal sensing)

    Location

    Stanford, CA

All Publications


  • Comparison of microparticle transport and deposition in nasal cavity of three different age groups. Inhalation toxicology Valerian Corda, J., Shenoy, B. S., Ahmad, K. A., Lewis, L., K, P., Rao, A., Zuber, M. 2024: 1-13

    Abstract

    Objective: The nasal cavity effectively captures the particles present in inhaled air, thereby preventing harmful and toxic pollutants from reaching the lungs. This filtering ability of the nasal cavity can be effectively utilized for targeted nasal drug delivery applications. This study aims to understand the particle deposition patterns in three age groups: neonate, infant, and adult.Materials and methods: The CT scans are built using MIMICS 21.0, followed by CATIA V6 to generate a patient-specific airway model. Fluid flow is simulated using ANSYS FLUENT 2021 R2. Spherical monodisperse microparticles ranging from 2 to 60 µm and a density of 1100 kg/m3 are simulated at steady-state and sedentary inspiration conditions.Results: The highest nasal valve depositions for the neonate are 25% for 20 µm, for infants, 10% for 50 µm, 15% for adults, and 15% for 15 µm. At mid nasal region, deposition of 15% for 20 µm is observed for infant and 8% for neonate and adult nasal cavities at a particle size of 10 and 20 µm, respectively. The highest particle deposition at the olfactory region is about 2.7% for the adult nasal cavity for 20 µm, and it is <1% for neonate and infant nasal cavities.Discussion and conclusions: The study of preferred nasal depositions during natural sedentary breathing conditions is utilized to determine the size that allows medication particles to be targeted to specific nose regions.

    View details for DOI 10.1080/08958378.2024.2312801

    View details for PubMedID 38343121

  • Clinical Study of Continuous Non-Invasive Blood Pressure Monitoring in Neonates. Sensors (Basel, Switzerland) Rao, A., Eskandar-Afshari, F., Weiner, Y., Billman, E., McMillin, A., Sella, N., Roxlo, T., Liu, J., Leong, W., Helfenbein, E., Walendowski, A., Muir, A., Joseph, A., Verma, A., Ramamoorthy, C., Honkanen, A., Green, G., Drake, K., Govindan, R. B., Rhine, W., Quan, X. 2023; 23 (7)

    Abstract

    The continuous monitoring of arterial blood pressure (BP) is vital for assessing and treating cardiovascular instability in a sick infant. Currently, invasive catheters are inserted into an artery to monitor critically-ill infants. Catheterization requires skill, is time consuming, prone to complications, and often painful. Herein, we report on the feasibility and accuracy of a non-invasive, wearable device that is easy to place and operate and continuously monitors BP without the need for external calibration. The device uses capacitive sensors to acquire pulse waveform measurements from the wrist and/or foot of preterm and term infants. Systolic, diastolic, and mean arterial pressures are inferred from the recorded pulse waveform data using algorithms trained using artificial neural network (ANN) techniques. The sensor-derived, continuous, non-invasive BP data were compared with corresponding invasive arterial line (IAL) data from 81 infants with a wide variety of pathologies to conclude that inferred BP values meet FDA-level accuracy requirements for these critically ill, yet normotensive term and preterm infants.

    View details for DOI 10.3390/s23073690

    View details for PubMedID 37050750

  • Optimal neuromonitoring techniques in neonates with hypoxic ischemic encephalopathy. Frontiers in pediatrics Chock, V. Y., Rao, A., Van Meurs, K. P. 2023; 11: 1138062

    Abstract

    Neonates with hypoxic ischemic encephalopathy (HIE) are at significant risk for adverse outcomes including death and neurodevelopmental impairment. Neuromonitoring provides critical diagnostic and prognostic information for these infants. Modalities providing continuous monitoring include continuous electroencephalography (cEEG), amplitude-integrated electroencephalography (aEEG), near-infrared spectroscopy (NIRS), and heart rate variability. Serial bedside neuromonitoring techniques include cranial ultrasound and somatic and visual evoked potentials but may be limited by discrete time points of assessment. EEG, aEEG, and NIRS provide distinct and complementary information about cerebral function and oxygen utilization. Integrated use of these neuromonitoring modalities in addition to other potential techniques such as heart rate variability may best predict imaging outcomes and longer-term neurodevelopment. This review examines available bedside neuromonitoring techniques for the neonate with HIE in the context of therapeutic hypothermia.

    View details for DOI 10.3389/fped.2023.1138062

    View details for PubMedID 36969281

    View details for PubMedCentralID PMC10030520

  • Micro- and nanoparticle transport and deposition in a realistic neonatal and infant nasal upper airway INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION Corda, J., Shenoy, B., Ahmad, K., Lewis, L., Prakashini, K., Rao, A., Zuber, M. 2023
  • Clinical decision support in the neonatal ICU. Seminars in fetal & neonatal medicine Rao, A., Palma, J. 2022: 101332

    Abstract

    Clinical Decision Support (CDS) tools help the healthcare team diagnose, monitor, and treat patients more efficiently and consistently by executing clinical practice guidelines and recommendations. As a result, CDS has a direct impact on the delivery and healthcare outcomes. This review covers the fundamental concepts, as well as the infrastructure needed to create a CDS tool and examples of its use in the neonatal setting. This article also serves as a primer on what to think about when proposing the development of a new CDS tool, or when upgrading an existing one. We also highlight important elements that influence CDS development, such as informatics methodologies, data and device interoperability, and regulation.

    View details for DOI 10.1016/j.siny.2022.101332

    View details for PubMedID 35428591

  • Advances in Non-Invasive Blood Pressure Monitoring. Sensors (Basel, Switzerland) Quan, X., Liu, J., Roxlo, T., Siddharth, S., Leong, W., Muir, A., Cheong, S., Rao, A. 2021; 21 (13)

    Abstract

    This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities.

    View details for DOI 10.3390/s21134273

    View details for PubMedID 34206457

  • Influence of enteral feeding and anemia on tissue oxygen extraction after red blood cell transfusion in preterm infants. Transfusion Goldstein, G. P., Rao, A. n., Ling, A. Y., Ding, V. Y., Chang, I. J., Chock, V. Y. 2020

    Abstract

    Understanding factors that impact tissue oxygen extraction may guide red blood cell (RBC) transfusion decision making in preterm infants. Our objective was to assess the influence of enteral feeding and anemia on cerebral and mesenteric oxygen saturation (Csat and Msat) and fractional tissue oxygen extraction (cFTOE and mFTOE) over the entire time course of RBC transfusion.Preterm, very low-birth-weight infants receiving RBC transfusions at a single center were enrolled. Near-infrared spectroscopy sensors measured Csat and Msat levels from an hour before transfusion to 24 hours after. During this period, changes in Csat, Msat, cFTOE, and mFTOE were described, and their association with enteral feeding status and pretransfusion degree of anemia were assessed using generalized estimating equations.RBC transfusion data from 31 preterm infants were included. Infants receiving enteral feeds exhibited lower pretransfusion Msat. Infants with pretransfusion hematocrit greater than 30% exhibited higher pretransfusion Csat and lower pretransfusion cFTOE. Such differences in baseline measurements persisted through 24 hours after transfusion. However, no statistically significant differences in oxygenation measures over time by enteral feeding or anemia status were identified.Compared to NPO, enteral feeding was associated with lower Msat; anemia (hematocrit ≤30%) was associated with lower Csat and higher cFTOE. Over the time course of RBC transfusion, trajectories of Csat, Msat, cFTOE and mFTOE did not differ by enteral feeding or anemia status.

    View details for DOI 10.1111/trf.15680

    View details for PubMedID 31984520

  • Textile Based Sensing Blanket for ECG Monitoring in the Intensive Care Unit Davis, C. L., Kao, T., Obi, A., Rao, A. V., Stoffel, N., IEEE IEEE. 2020: 4551–54
  • Liver Failure and Rash in a 6-week-old Girl PEDIATRICS IN REVIEW Mediratta, R., Schwenk, H., Rao, A., Chitkara, R. 2018; 39 (6): 315–U22

    View details for PubMedID 29858298

  • Comparing two anesthesia information management system user interfaces: a usability evaluation CANADIAN JOURNAL OF ANESTHESIA-JOURNAL CANADIEN D ANESTHESIE Wanderer, J. P., Rao, A. V., Rothwell, S. H., Ehrenfeld, J. M. 2012; 59 (11): 1023-1031

    Abstract

    Anesthesia information management systems (AIMS) have been developed by multiple vendors and are deployed in thousands of operating rooms around the world, yet not much is known about measuring and improving AIMS usability. We developed a methodology for evaluating AIMS usability in a low-fidelity simulated clinical environment and used it to compare an existing user interface with a revised version. We hypothesized that the revised user interface would be more useable.In a low-fidelity simulated clinical environment, twenty anesthesia providers documented essential anesthetic information for the start of the case using both an existing and a revised user interface. Participants had not used the revised user interface previously and completed a brief training exercise prior to the study task. All participants completed a workload assessment and a satisfaction survey. All sessions were recorded. Multiple usability metrics were measured. The primary outcome was documentation accuracy. Secondary outcomes were perceived workload, number of documentation steps, number of user interactions, and documentation time. The interfaces were compared and design problems were identified by analyzing recorded sessions and survey results.Use of the revised user interface was shown to improve documentation accuracy from 85.1% to 92.4%, a difference of 7.3% (95% confidence interval [CI] for the difference 1.8 to 12.7). The revised user interface decreased the number of user interactions by 6.5 for intravenous documentation (95% CI 2.9 to 10.1) and by 16.1 for airway documentation (95% CI 11.1 to 21.1). The revised user interface required 3.8 fewer documentation steps (95% CI 2.3 to 5.4). Airway documentation time was reduced by 30.5 seconds with the revised workflow (95% CI 8.5 to 52.4). There were no significant time differences noted in intravenous documentation or in total task time. No difference in perceived workload was found between the user interfaces. Two user interface design problems were identified in the revised user interface.The usability of anesthesia information management systems can be evaluated using a low-fidelity simulated clinical environment. User testing of the revised user interface showed improvement in some usability metrics and highlighted areas for further revision. Vendors of AIMS and those who use them should consider adopting methods to evaluate and improve AIMS usability.

    View details for DOI 10.1007/s12630-012-9771-z

    View details for Web of Science ID 000310340200003

    View details for PubMedID 23055030

  • Evolution of data management tools for managing self-monitoring of blood glucose results: a survey of iPhone applications. Journal of diabetes science and technology Rao, A., Hou, P., Golnik, T., Flaherty, J., Vu, S. 2010; 4 (4): 949-957

    Abstract

    Studies have indicated that sharing of self-monitoring of blood glucose (SMBG) data and subsequent feedback from the health care provider (HCP) can help achieve glycemic goals such as a reduction in glycated hemoglobin. Electronic SMBG data management and sharing tools for the PC and smartphones may help in reducing the effort to manage SMBG data.We reviewed software and top-ranking applications (Apps) for the iPhone platform to document the variety of useful features. Additionally, in an attempt to assess metrics such as task analysis and user friendliness of diabetes Apps, we observed and surveyed patients with diabetes as they recorded and relayed sample SMBG results to their hypothetical HCP using three Apps.Observation and survey demonstrated that the WaveSense Diabetes Manager allowed the participants to complete preselected SMBG data entry and relay tasks faster than other Apps. The survey revealed patient behavior patterns that would be useful in future App development.Being able to record, analyze, seamlessly share, and obtain feedback on the SMBG data using an iPhone/iTouch App might potentially benefit patients. Trends in SMBG data management and the possibility of having interoperability of blood glucose monitors and smartphones may open up new avenues of diabetes management for the technologically savvy patient.

    View details for PubMedID 20663461

  • Individuals achieve more accurate results with meters that are codeless and employ dynamic electrochemistry. Journal of diabetes science and technology Rao, A., Wiley, M., Iyengar, S., Nadeau, D., Carnevale, J. 2010; 4 (1): 145-150

    Abstract

    Studies have shown that controlling blood glucose can reduce the onset and progression of the long-term microvascular and neuropathic complications associated with the chronic course of diabetes mellitus. Improved glycemic control can be achieved by frequent testing combined with changes in medication, exercise, and diet. Technological advancements have enabled improvements in analytical accuracy of meters, and this paper explores two such parameters to which that accuracy can be attributed.Four blood glucose monitoring systems (with or without dynamic electrochemistry algorithms, codeless or requiring coding prior to testing) were evaluated and compared with respect to their accuracy.Altogether, 108 blood glucose values were obtained for each system from 54 study participants and compared with the reference values. The analysis depicted in the International Organization for Standardization table format indicates that the devices with dynamic electrochemistry and the codeless feature had the highest proportion of acceptable results overall (System A, 101/103). Results were significant when compared at the 10% bias level with meters that were codeless and utilized static electrochemistry (p = .017) or systems that had static electrochemistry but needed coding (p = .008).Analytical performance of these blood glucose meters differed significantly depending on their technologic features. Meters that utilized dynamic electrochemistry and did not require coding were more accurate than meters that used static electrochemistry or required coding.

    View details for PubMedID 20167178

  • A simple approach for the computation of multiple periodicities in biological time series BIOLOGICAL RHYTHM RESEARCH Rao, A. V., Sharma, V. K. 2002; 33 (5): 487-502