Networked and Embedded Systems Laboratory

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The severity and degree of recovery for a traumatic brain injury can be assessed by the myotatic stretch reflex. Descending supraspinal input provides inhibitory modulation of the myotatic stretch reflex. A hyperactive reflex response is correlated with spasticity, which also can be correlated with the degree of damage to the supraspinal input, in essence assessing the severity of traumatic brain injury. The myotatic stretch reflex is clinically evaluated by the Ashworth scale (1 to 5). A rating of 1 is nominal and 5 representing the greatest level of tightness.  The Ashworth scale however lacks temporal data and also may vary in terms of interpretation. The solution is a fully quantified evaluation system of the myotatic stretch reflex. A piezoelectric hammer with a predetermined force input, based on original potential energy will quantify the input. MEMS accelerometer and wearable computers can assist us with quantifying the output. Our proposed wearable computer architecture is a platform for health monitoring, based on wireless sensor networks.  This architecture is a network enabled system that supports various wearable sensors and contains on-board general computing capabilities for executing individually tailored event detection, alerts, and network communication with various medical informatics services. The MEMS accelerometers are attached to a set anchor point near the ankle.  The reflex response can be temporally averaged by integrating acceleration from initial time to final time. The quantified data collected from MEMS accelerometers is transmitted a portable computer (i.e. a Pocket PC).  The myotatic stretch reflex can subsequently be normalized by the ratio of averaged acceleration of ipsilesional to contralateral limb. Results indicate that the spastic ipsilesional limb produces a higher acceleration relative to contralateral limb.

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