The ability of doctors to correctly diagnose a patient is one of the most critical components of successful medical care. All events that occur from that point on are dictated by the diagnosis the physician makes. Current diagnosis modality is a result of Q&A with the patient regarding symptoms, taking of vital signs, and other tests such as blood work, MRIs, or CT scans. Such diagnosis is conducted with snap shot information taken in an artificial setting. This approach is prone to errors due to the natural variability in the physiological parameters that are being monitored and does not allow physicians to assess transient, episodic symptoms that often leave patients with irreparable physical damage. Technology that provides real-time continuous monitoring of a patient's state of health would provide physicians with information leading to a more realistic picture of a patient's lifestyle and thus enable doctors to diagnose more accurately.
With the advent of implantable intervention devices (e.g. implantable cardioverter defibrillator) and in vivo sensors (e.g. continuous glucose monitoring system), patients have enjoyed the immediate benefits of constant monitoring in many areas including sudden cardiac deaths reduction and diabetic patient lifestyles improvements. Building on the preliminary success of closed-loop monitoring, our next step is to enable simultaneous gathering of patients' long-term vital signs and physiological information in a natural environment.
Our approach is to develop an implantable sensor network based on distributed network technology and in vivo sensors. Our system has three components: 1) miniaturized sensor module encases and protects the various physical and chemical MEMS sensors in a biocompatible package; 2) sensor node contains our power supply, signal conditioning circuit and wireless transceiver, and 3) PDA provides the communication hub where testing parameters are managed and physiological data are stored and displayed. Individually each sensor module can independently record critical vital signs and physiological parameters of the monitored system. Together, the distributed sensor network acts as a collective monitor of systemic symptoms. Based on our database, we may assess valuable interrelated effects of physiological profiles under specific perturbations not possible before. Our first generation of this concept is a minimally invasive implantable pressure sensing system to assess the gross pressure change in the bladder and renal pelvis per degree of ureteropelvic obstruction. Our sensor module, which can be adapted for other types of physiological sensors, is connected by an 8F catheter to the sensor node. The node has multi-input/output channels, quarter-sized form factor, 433MHz transceiver, and programmable power states suitable to extend measurement periods after initial trauma. Our PDA identifies, receives, stores, and displays individual sensor node signal. It also provides a communication interface where users may remotely monitor and program the sampling rate, on/sleep/off period of the distributed sensor nodes.
Current work is being done on a very small pressure sensitive catheter (1-2 French), as well as a pH sensor/glucose sensor/CO2 sensor.
Peter Schulam, MD, Department of Urology
Jacob Schmidt, PhD, Department of Bioengineering
Graduate Students: Robert Tan, Department of Bioengineering
Medical Resident: Timothy McClure, MD, Department of Urology
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