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Glycemic control through titration of insulin dosing remains the mainstay of diabetes mellitus treatment. Insulin therapy is generally divided into dosing with long- and short-acting insulin, where long-acting insulin provides basal coverage and short-acting insulin supports glycemic excursions associated with eating. The dosing of short-acting insulin often involves several steps for the user including blood glucose measurement and integration of potential carbohydrate loads to inform safe and appropriate dosing. The significant burden placed on the user for blood glucose measurement and effective carbohydrate counting can manifest in substantial effects on adherence. Through the application of computer vision, we have developed a smartphone-based system that is able to detect the carbohydrate load of food by simply taking a single image of the food and converting that information into a required insulin dose by incorporating a blood glucose measurement. Moreover, we report the development of comprehensive all-in-one insulin delivery systems that streamline all operations that peripheral devices require for safe insulin administration, which in turn significantly reduces the complexity and time required for titration of insulin. The development of an autonomous system that supports maximum ease and accuracy of insulin dosing will transform our ability to more effectively support patients with diabetes.

N95 filtering facepiece respirators (FFR) and surgical masks are essential in reducing airborne disease transmission, particularly during the COVID-19 pandemic. However, currently available FFR's and masks have major limitations, including masking facial features, waste, and integrity after decontamination. In a multi-institutional trial, we evaluated a transparent, elastomeric, adaptable, long-lasting (TEAL) respirator to evaluate success of qualitative fit test with user experience and biometric evaluation of temperature, respiratory rate, and fit of respirator using a novel sensor. There was a 100% successful fit test among participants, with feedback demonstrating excellent or good fit (90% of participants), breathability (77.5%), and filter exchange (95%). Biometric testing demonstrated significant differences between exhalation and inhalation pressures among a poorly fitting respirator, well-fitting respirator, and the occlusion of one filter of the respirator. We have designed and evaluated a transparent elastomeric respirator and a novel biometric feedback system that could be implemented in the hospital setting., NIH(Grants K23DA044874, R44DA051106), NIH (Grants K23DA044874, R44DA051106, 5T32DK007191-4)

The COVID-19 pandemic has accelerated methods to facilitate contactless evaluation of patients in hospital settings. By minimizing unnecessary in-person contact with individuals who may have COVID-19 disease, healthcare workers (HCW) can prevent disease transmission, and conserve personal protective equipment. Obtaining vital signs is a ubiquitous task that is commonly done in-person. To eliminate the need for in-person contact for vital signs measurement in the hospital setting, we developed Dr. Spot, an agile quadruped robotic system that comprises a set of contactless monitoring systems for measuring vital signs and a tablet computer to enable face-to-face medical interviewing. Dr. Spot is teleoperated by trained clinical staff to facilitate enhanced telemedicine. Specifically, it has the potential to simultaneously measure skin temperature, respiratory rate, heart rate, and blood oxygen saturation simultaneously while maintaining social distancing from the patients. This is important because fluctuations in vital sign parameters are commonly used in algorithmic decisions to admit or discharge individuals with COVID-19 disease. Here, we deployed Dr. Spot in a hospital setting with the ability to measure the vital signs from healthy volunteers from which the measurements of elevated skin temperature screening, respiratory rate, heart rate, and SpO2 were carefully verified with ground-truth sensors.

ObjectiveTo develop and test a new reusable, sterilisable N95 filtering facepiece respirator (FFR)-comparable face mask, known as the Injection Molded Autoclavable, Scalable, Conformable (iMASC) system, given the dire need for personal protective equipment within healthcare settings during the COVID-19 pandemic.DesignSingle-arm feasibility study.SettingEmergency department and outpatient oncology clinic.ParticipantsHealthcare workers who have previously undergone N95 fit testing.InterventionsFit testing of new iMASC system.Primary and secondary outcome measuresPrimary outcome is success of fit testing using an Occupational Safety and Health Administration (OSHA)-approved testing method, and secondary outcomes are user experience with fit, breathability and filter replacement.ResultsTwenty-four subjects were recruited to undergo fit testing, and the average age of subjects was 41 years (range of 21–65 years) with an average body mass index of 26.5 kg/m2. The breakdown of participants by profession was 46% nurses (n=11), 21% attending physicians (n=5), 21% resident physicians (n=5) and 12% technicians (n=3). Of these participants, four did not perform the fit testing due to the inability to detect saccharin solution on premask placement sensitivity test, lack of time and inability to place mask over hair. All participants (n=20) who performed the fit test were successfully fitted for the iMASC system using an OSHA-approved testing method. User experience with the iMASC system, as evaluated using a Likert scale with a score of 1 indicating excellent and a score of 5 indicating very poor, demonstrated an average fit score of 1.75, breathability of 1.6, and ease of replacing the filter on the mask was scored on average as 2.05.ConclusionsThe iMASC system was shown to successfully fit multiple different face sizes and shapes using an OSHA-approved testing method. These data support further certification testing needed for use in the healthcare setting.

There is a dire need for personal protective equipment (PPE) within healthcare settings during the COVID-19 pandemic. In particular, single use disposable N95 face masks have been limited in supply. We have developed an Injection Molded Autoclavable, Scalable, Conformable (iMASC) system for aerosol-based protection. The iMASC system was designed as a reusable liquid silicone rubber mask with disposable N95 filter cartridges that can fit most face sizes and shapes. This system reduced the amount of N95 filter while preserving breathability and fit. Using finite element analysis, we demonstrated mask deformation and reaction forces from facial scans of twenty different wearers. In addition, we validated these findings by successful fit testing in twenty participants in a prospective clinical trial. The iMASC system has the potential to protect our healthcare workers with a reusable N95-comparable face mask that is rapidly scalable.