• WEARABLE BIOSENSING LAB conducts interdisciplinary research between biomedical sensors and wearable embedded systems. The overarching goal of the lab is to simplify the design of point-of-care medical devices to a point where individuals are enveloped by unobtrusive health sensing elements for tele-monitoring disease symptoms and for remote healthcare management. 

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NSF CAREER: CPS: Internet of Wearable E-Textiles for Telemedicine

  • This CAREER project aims to translate the smart electronic textile (e-textile) technologies to fill the need for telemedicine. The project will result into an in-home, wearable internet-of-things hub (referred to as "IoT-Hub") consisting of smart e-textiles such as e-gloves, e-socks, and companion computing devices for data analytics, storage, and communications to the cloud servers of hospitals.

  • [Funded by NSF CAREER1652538 ]

NIH: anEAR : Android Electrically Activated Recorder

  • This is a collaborative project with Rhode Island Hospital to understand THE INTERPLAY OF SOCIAL CONTEXT AND PHYSIOLOGY ON PSYCHOLOGICAL OUTCOMES IN TRAUMA-EXPOSED ADOLESCENTS. We implement and deploy wearable systems to monitor the physiological and personal environment indicators in participants with PTSD. 

  • [Funded by NIH : R01MH108641 ]

NSF CRII: Brain-Body Sensor Fusion

  • The functional coupling between the activities of brain and muscle can be measured as cortico-muscular coherence (CMC). This project is aimed at  integrating fNIRS neuroimaging with body's motion dynamics to study individuals with movement disorders.

  • [Funded by NSF CRII: 1565962]

NSF EpSCoR: Portable Multimodal (fNIRS-EEG) Neuromonitoring

  • This project performs multimodal neuroimaging noninvasively by placing an array of electrodes performing  functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) concurrently.

  • [Funded by NSF RII Track-2 FEC: 1539068]

Speech Treatment & Therapy Through Mobile Devices

  • This is a telehealth project  that uses smartphone sensors to facilitate efficient management of speech treatments in remote settings such as homes.

  • [Funded by Rhode Island Foundation Medical Research]

Wearable Internet-of-Things

  • The emerging field of Internet-of-Things (IoT) blends mobile computing systems, advanced communication technologies, and cloud computing. If merged with wearable technologies, IoT could potentially provide personalized interventions to anyone, anytime, and anywhere. Our lab has designed a unique Wearable IoT framework that interconnects wearable sensors, smartphones and cloud servers to enable personalized healthcare. WIoT helps physicians to leverage wearable sensors in their interventions to monitor multidimensional symptoms of patients from their body, brain and behaviors.

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[Funded by URI Council of Research]



SPARK: Smartphone/Smartwatch System for Parkinson Patients

  • Parkinson disease (PD) is a neurodegenerative disorder afflicting more than 1 million aging Americans, incurring $23 billion in annual medical costs in the U.S. alone. Efficient management of PD requires complex medication regimens specifically titrated to individuals’ needs. These personalized regimens are difficult to maintain for the patient and difficult to prescribe for a physician in the few minutes available during office visits. Diverging from current form of laboratory-ridden technologies, SPARK framework is built upon a synergistic combination of Smartphone and Smartwatch in monitoring multidimensional symptoms – such as facial tremors, dysfunctional speech, limb dyskinesia, and gait abnormalities. 
[Funded by Pitt Innovation Challenge] [Video]

Pulse-Glasses: A Cloud-Connected Eyewear for Health Monitoring

  • Pulse-Glasses technology is a pair of smartglasses to monitor human health unobtrusively and continuously. It uses wearable IoT framework to manage sensors, computations and communications. 

Ubiquitous Intelligence in Behavioral Interventions

  • Behavioral disorders demand more efficient technology to analyze patients' emotional health as well as their compliance with prescribed therapy. Mobile Health (mHealth) is one of the active research areas and offers a remarkable opportunity in the field of psychiatry to evaluate patient’s emotional health. Smartphones, today, come with multiple sensors and could help to understand specific signatures of mental illness, if ubiquitous intelligence and computing would be injected in smartphones. This project aims at sensing emotions, mental states, and behaviors of patients with mental disorders.

  • [Funded by Penn Infrastructure Technology Alliance]

Multimodal Wearable Health Monitoring [Completed in 2010]

  • Along with Worldwide population growth, there has been increment in the number of individuals with chronic diseases such as diabetes, cardiovascular disorders, sleeping disorder, vestibular disorder, and many others. We focused on the need of multi-sensory wearable health monitoring as well as presented a design of such a monitor using energy-efficient, high-performance embedded processors. We designed miniaturized wearable health sensors that synced the medical data to such processors for real-time signal processing. This research was highly interdisciplinary in nature and applicable to the emerging fields of technology such as Mobile Health (mHealth), Ambient Assisted Living (AAL), Pervasive Health, Ubiquitous/Wearable Computing and Embedded Computing.

ActiveBelt: Textile-based Wearable ECG System [Completed in 2010]

  • Life-threatening cardiovascular diseases require early detection or diagnosis. A standard procedure, long-term ECG monitoring of cardiac patients is currently the best way to reduce the number of heart failures. Dry and washable textile electrodes embedded in comfortable garment or in a wearable chest belt have been proven very effective for a long-term ECG monitoring in comparison to the conventional Ag/AgCl electrodes. ActiveBelt was a wearable ECG chest belt, which contained stitched textile electrodes for ECG detection and analog preprocessing circuits embedded in tiny cell-phone plugs. We have achieved promising results of textile electrodes along with our hardware and embedded system in conveying a better ECG signal quality having a clinical significance for a long-term ECG recording in a daily life.

Miniaturized Cerebral Oximetry [Completed in 2011]

  • Cerebral injury due to hypoxia is one of the most dreadful outcomes of surgical procedures. NIRS based cerebral oximetry is known to be a noninvasive and safe method to monitor cerebral metabolism and oxygen consumption. In cerebral oximetry, A sensor patch on the forehead injects near-infrared light through the different layers of the skull and detects the backscattered light intensities. We developed a novel design of a miniaturized cerebral oximeter, which consisted of small-scale analog frontend linking to a high-performance embedded system for onboard data processing.  The heart of the system was an OMAP3530 dual core processor, which produced the driving pulses for the light source and acquired the detected data as a function of the wavelengths to calculate and display rSO2 (brain oxygen) value.


IMMERSIVE ENVIRONMENTS: Navigable 3D Visualizations of Real-world Spaces

  • Conceptually, immersive environments virtually surround individuals such that they psychologically feel themselves to be covered by an environment providing continuous visual stimuli, and feel their presence at the remote environment. Today, the 3D visualization and exploration of real-world spaces on the computer screen is very much a product of panorama photography and its applications in the field of computing and human-computer interaction (HCI). This project was a design, implementation, and deployment of the cloud-assisted interface framework for immersive  environment that can be ported to personal computing devices as well as larger networked displays, such as retail kiosks and television 

PANOPTES: Crowd-sourced Cars

  • The project built upon the successful and highly visible deployed mobile 311 efforts (with iBurgh being the nation’s first mobile 311 app) and the crowdsourced snow-removal HowsMyStreet platform. By employing cloud-based crowdsourcing of the automated reports from the various embedded platforms in all of the vehicles under test, and then correlating this data potentially with the crowdsourced information from human input, this project was aimed at providing a more accurate, actionable picture of the driveability of the roads under snow-storm and pothole-ridden conditions. 

MetaBot: Schedulable Behaviors in Mobile Robots 

  • Mobile service robots are mission-oriented machines, built to perform actions associated with desired goals. Accordingly, the mobile robot requires knowledge of how to coordinate several actions relative to environmental and timing constraints. MetaBot, a sensor-rich mobile robot, was designed to autonomously navigate indoor environments and execute micro-navigational tasks, commanded by human operators or scheduled at predefined time-intervals.