Our device correlates data from the impedance spectra of the lower leg with the pathophysiological changes observed in CECS and as such will serve as a non-invasive diagnostic tool for the condition that is also capable of taking real-time measurements. The finalized device will comprise two wearable sleeves, each surrounded by a set of electrodes which have been strategically placed to allow for the construction of a 2D image of the axial plane of the lower leg using impedance tomography. The multiple electrodes are connected via a multiplexer circuit to an AD5940 Impedance Spectroscopy Chip (obtained from Analog Devices Inc.). The chip itself will be interfaced with a system controller (Arduino Mega, Raspberry Pi or equivalent). The AD5940 impedance spectroscopy chip is designed to input current of varying frequencies to a set of electrodes on the skin surface and measures the voltage response of the tissue through a seperate set of electrodes. The voltage response is used to calculate an impedance value for each of input current frequency (impedance spectra). The impedance spectra will be stored on the controller, which will have a bluetooth functionality that can be programmed to convey data to a nearby desktop computer. Impedance spectra of the lower leg from before and immediately after exercise will be analysed in MATLAB using a machine learning algorithm designed/trained to identify the differences in impedance spectra for normal and compartment syndrome leg compartments. Impedance tomography may also be used to improve measurement specificity. An intuitive user-interface will be created on a desktop computer, designed to let the physician know whether or not the patient has compartment syndrome, and if possible, the extent/severity of the syndrome. The principles of operation, circuit diagrams and CAD diagrams of our proposed device are provided in the proceeding sections.