Detection of biological signals from a live mammalian muscle using a diamond quantum sensor

• URL: http://arxiv.org/abs/2008.01002v1
• Date: Mon, 3 Aug 2020 16:40:44 GMT
• Title: Detection of biological signals from a live mammalian muscle using a diamond quantum sensor
• Authors: James Luke Webb, Luca Troise, Nikolaj Winther Hansen, Christoffer Olsson, Adam Wojciechowski, Jocelyn Achard, Ovidiu Brinza, Robert Staacke, Michael Kieschnick, Jan Meijer, Axel Thielscher, Jean-Francois Perrier, Kirstine Berg-Sorensen, Alexander Huck, Ulrik Lund Andersen
• Abstract summary: We show an alternative technique for detecting magnetic fields generated by the current from action potentials in living tissue using nitrogen vacancy centres in diamond. We show these measurements can be performed in an ordinary, unshielded lab environment and that the signal can be easily recovered by digital signal processing techniques.
• Score: 41.91891973513696
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The ability to perform noninvasive, non-contact measurements of electric signals produced by action potentials is essential in biomedicine. A key method to do this is to remotely sense signals by the magnetic field they induce. Existing methods for magnetic field sensing of mammalian tissue, used in techniques such as magnetoencephalography of the brain, require cryogenically cooled superconducting detectors. These have many disadvantages in terms of high cost, flexibility and limited portability as well as poor spatial and temporal resolution. In this work we demonstrate an alternative technique for detecting magnetic fields generated by the current from action potentials in living tissue using nitrogen vacancy centres in diamond. With 50pT/$\sqrt{Hz}$ sensitivity, we show the first measurements of sensing from mammalian tissue with a diamond sensor using mouse muscle optogenetically activated with blue light. We show these measurements can be performed in an ordinary, unshielded lab environment and that the signal can be easily recovered by digital signal processing techniques.

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