A multiport vector network analyzer with high-precision and realtime capabilities for brain imaging and stroke detection. Issue 5 (22nd March 2018)

• Record Type: Journal Article
• Authors: Poltschak, Sebastian; Freilinger, Markus; Feger, Reinhard; Stelzer, Andreas; Hamidipour, Abouzar; Henriksson, Tommy; Hopfer, Markus; Planas, Ramon; Semenov, Serguei
• Editors: Kallfass, Ingmar; Vossiek, Martin; A. Hein, Matthias
• Is Part Of: International journal of microwave and wireless technologies. Volume 10:Issue 5/6(2018)
• Page Start: 605
• Page End: 612
• Publication Date: 2018-03-22
• Subjects: Biomedical applications, -- microwave measurements; Wireless communication systems -- Periodicals; Microwave circuits -- Periodicals; Radio frequency -- Periodicals; 621.381305
• DOI: 10.1017/S1759078718000363
• Languages: English
• ISSNs: 1759-0787

Abstract

Abstract: Medical imaging is of great importance for patients affected by stroke. Since an early examination of the patient is necessary for successful recovery, there is room to improve the existing capabilities of analysis. Common systems like magnetic resonance imaging or computed tomography are precise, but stationary, and therefore, not ideally suited for the early analysis of stroke. The presented multiport vector network analyzer system uses electromagnetic tomography (EMT) as an alternative imaging technique. It consists of a network of distributed electronic sensor nodes which improve important parameters: the parallel measurement setup reduces the measurement time as low as 160 ms for a 200-port S-parameter matrix and it is capable of measuring signal levels down to − 150 dBm. The electronics allow a compact, movable packaging, leading the way for future portable devices. The detection of stroke models was examined by test measurements of a phantom. The data was analyzed by the help of an inverse reconstruction algorithm. The possibility of building portable setups which can be even applied to patients inside an ambulance, makes EMT a suitable alternative for early stroke detection. It can help in shortening the recovery of patients, by providing an early analysis of the brain.