Brain Sensing Technology Provides Real-Time Diagnosis
- Friday, 01 July 2011
Portable system identifies, assesses, and monitors cerebral abnormalities, including stroke, traumatic brain injury, and sports concussion.
Every 21 seconds, someone suffers a serious brain injury, including stroke, trauma, or concussion. Until now, there has been no way to quickly and reliably diagnose these calamities.
A portable brain diagnostic system has been developed for non-invasively detecting brain abnormalities quickly. Two completed pilot studies have demonstrated the potential of the technology to give clinicians timely and reliable data in the event of stroke, brain injury, or the presence of a cerebrovascular abnormality.
This company’s initial focus is in identifying and monitoring stroke victims in the emergency room and neuro critical care setting, providing timely information that will reduce the time to initial treatment and response to emergency.
For the military, the company ultimately hopes that the system will assess traumatic brain injury (TBI) in the far forward positions of a battlefield, thus allowing critically injured soldiers to reach treatment facilities in the shortest possible time.
The technology draws on decades of submarine technology; specifically sensors and signal processing. As blood flows into the brain during each heartbeat, a pressure wave emanates from the vessels outward in all directions. Each time the heart beats and surges blood into the vascular system of the head, the brain is set into motion. Each and every cerebral blood vessel and the brain matter itself respond with an ever-so-slight sympathetic motion that has structurally defined characteristics — veins expand and contract, aneurysms oscillate and stenosis restrict and confine; each produces a unique pressure “signature” that can be both qualified and quantified by the system. The accelerometers record this waveform with time-synchronized, high-resolution digitizers. The repeating waveform is averaged using proprietary averaging techniques that preserve detailed signature data of force and response in terms of flow and structure during both systole and diastole periods.
The portable Jan Medical brain sensing system consists of three primary components: a reusable headset with sensors, a controller/signal processor, and algorithms. The headset is responsible for mounting the sensors against the head and acquiring signals from the brain; the processor controls the measurement process and interfaces with the operator; and the algorithms are Jan Medical’s proprietary diagnostic and prognostic intellectual property.
Six sensors mounted via a headset apply the proper pressure of the sensors to the skin. These sensors are mounted above each of the major plates of the skull.
The sensors are digitized by individual synchronized 24 bit low noise analog to digital converters (ADC). Output from each sensor is averaged over 20 to 40 heartbeats, generally in less than one minute.
The system can be used for rapid diagnosis, typically in under a few minutes, or used for continuous monitoring of changes in blood flow or brain structure over hours, days, or weeks as necessary.
Jan Medical analyzed the waveforms from patients with known conditions of the brain to develop signal processing algorithms that are then used to train data mining software. The developed algorithms were then used on the complete set of data to determine the sensitivity and specificity of a patient having a stroke condition or a concussion.
The Johns Hopkins stroke trial recruited patients (N=40) with all types of stroke and related conditions including multiple conditions within a single patient. The primary endpoint was to develop signal processing algorithms for strokes and vascular abnormalities. The patient’s conditions were verified by imaging studies. The Jan Medical signal analysis team developed algorithms for four conditions: Aneurysm, Ischemia, Ischemia/Stenosis, and Structural. Structural includes AVM, AVF, DAVF and DVAM. From these results, an algorithm was developed for stroke or no stroke. The algorithm was trained with 35 stroke patients and 18 normal subjects. The algorithm was tested with an additional 50 normal subjects and three additional stroke patients. The results included 37 true positive, 1 false negative, 74 true negative and 6 false positive; the sensitivity for detecting a stroke was 97% and specificity for detecting no stroke at 93%.
This technology was done by Jan Medical, Mountain View, CA. For more information, visit http://info.hotims.com/34456-193.