Search for: All records

Abstract Frequent prothrombin time (PT) and international normalized ratio (INR) testing is critical for millions of people on lifelong anticoagulation with warfarin. Currently, testing is performed in hospital laboratories or with expensive point-of-care devices limiting the ability to test frequently and affordably. We report a proof-of-concept PT/INR testing system that uses the vibration motor and camera on smartphones to track micro-mechanical movements of a copper particle. The smartphone system computed the PT/INR with inter-class correlation coefficients of 0.963 and 0.966, compared to a clinical-grade coagulation analyzer for 140 plasma samples and demonstrated similar results for 80 whole blood samples using a single drop of blood (10 μl). When tested with 79 blood samples with coagulopathic conditions, the smartphone system demonstrated a correlation of 0.974 for both PT/INR. Given the ubiquity of smartphones in the global setting, this proof-of-concept technology may provide affordable and effective PT and INR testing in low-resource environments. 

Abstract Background Tympanometry is used as part of a battery of tests for screening of middle ear function and may help diagnose middle ear disorders, but remains available only on expensive test equipment. Methods We report a low-cost smartphone-based tympanometer system that consists of a lightweight and portable attachment to vary air pressure in the ear and measure middle ear function. The smartphone displays a tympanogram and reports peak acoustic admittance in realtime. Our programmable and open-source system operates at 226 Hz and was tested on 50 pediatric patient ears in an audiology clinic in parallel with a commercial tympanometer. Results Our study shows an average agreement of 86 ± 2% between the 100 tympanograms produced by the smartphone and commercial device when five pediatric audiologists classified them into five classes based on the Liden and Jerger classification. Conclusion Given the accessibility and prevalence of budget smartphones in developing countries, our open-source tool may help provide timely and affordable screening of middle ear disorders. 

Abstract Overdoses from non-medical use of opioids can lead to hypoxemic/hypercarbic respiratory failure, cardiac arrest, and death when left untreated. Opioid toxicity is readily reversed with naloxone, a competitive antagonist that can restore respiration. However, there remains a critical need for technologies to administer naloxone in the event of unwitnessed overdose events. We report a closed-loop wearable injector system that measures respiration and apneic motion associated with an opioid overdose event using a pair of on-body accelerometers, and administers naloxone subcutaneously upon detection of an apnea. Our proof-of-concept system has been evaluated in two environments: (i) an approved supervised injection facility (SIF) where people self-inject opioids under medical supervision and (ii) a hospital environment where we simulate opioid-induced apneas in healthy participants. In the SIF (n= 25), our system identified breathing rate and post-injection respiratory depression accurately when compared to a respiratory belt. In the hospital, our algorithm identified simulated apneic events and successfully injected participants with 1.2 mg of naloxone. Naloxone delivery was verified by intravenous blood draw post-injection for all participants. A closed-loop naloxone injector system has the potential to complement existing evidence-based harm reduction strategies and, in the absence of bystanders, help make opioid toxicity events functionally witnessed and in turn more likely to be successfully resuscitated. 

The presence of middle ear fluid is a key diagnostic marker for two of the most common pediatric ear diseases: acute otitis media and otitis media with effusion. We present an accessible solution that uses speakers and microphones within existing smartphones to detect middle ear fluid by assessing eardrum mobility. We conducted a clinical study on 98 patient ears at a pediatric surgical center. Using leave-one-out cross-validation to estimate performance on unseen data, we obtained an area under the curve (AUC) of 0.898 for the smartphone-based machine learning algorithm. In comparison, commercial acoustic reflectometry, which requires custom hardware, achieved an AUC of 0.776. Furthermore, we achieved 85% sensitivity and 82% specificity, comparable to published performance measures for tympanometry and pneumatic otoscopy. Similar results were obtained when testing across multiple smartphone platforms. Parents of pediatric patients ( n = 25 ears) demonstrated similar performance to trained clinicians when using the smartphone-based system. These results demonstrate the potential for a smartphone to be a low-barrier and effective screening tool for detecting the presence of middle ear fluid.