Recent developments in spintronics materials and physics are promising to develop a new type of magnetic sensors which can be embedded into the silicon chips. These neuromorphic sensing chips will be designed to capture the biomagnetic signals from active biological tissue exploited as brain-machine interface. They lead to machines that are able to sense and interact with the world in humanlike ways and able to accelerate years of fitful advance in artificial intelligence. To detect the weak biomagnetic signals, this work aims to develop a CMOS-compatible spintronic sensor based on the magnetoresistive (MR) effect. As an alternative to bulky superconducting quantum interference device (SQUID) systems, the miniaturised spintronic devi...
Magnetism‐based systems are widely utilized for sensing and imaging biological phenomena, for exampl...
In order to measure extremely weak magnetic fields, such as those produced by the neuronal activity ...
Spintronics has gone through substantial progress due to its applications in energy-efficient memory...
Recent developments in spintronics materials and physics are promising to develop a new type of mag...
Spintronic devices have been proposed over the past decade for various biomedical applications. Thes...
MagnetoMyoGraphy (MMG) with superconducting quantum interference devices (SQUIDs) enabled the measur...
Neuromorphic computing uses basic principles inspired by the brain to design circuits that perform a...
In this work an alternative neuroscience tool for electromagnetic measurements of neurons at the lev...
Neuromorphic studies, which are inspired by the way the human brain works with the extremely low-pow...
This paper presents a CMOS readout circuit for an integrated and highly-sensitive tunnel-magnetores...
Artificial intelligence has become indispensable in modern life, but its energy consumption has beco...
Integrated spintronic biochip platforms are being developed for portable, point-of-care, diagnostic ...
Magnetoencephalography has been established nowadays as a crucial in vivo technique for clinical and...
An alternative neuroscience tool for magnetic field detection is described in this work, providing b...
Spintronic sensors, that are based on the tunnellingmagnetoresistive (TMR) effect, have been utilize...
Magnetism‐based systems are widely utilized for sensing and imaging biological phenomena, for exampl...
In order to measure extremely weak magnetic fields, such as those produced by the neuronal activity ...
Spintronics has gone through substantial progress due to its applications in energy-efficient memory...
Recent developments in spintronics materials and physics are promising to develop a new type of mag...
Spintronic devices have been proposed over the past decade for various biomedical applications. Thes...
MagnetoMyoGraphy (MMG) with superconducting quantum interference devices (SQUIDs) enabled the measur...
Neuromorphic computing uses basic principles inspired by the brain to design circuits that perform a...
In this work an alternative neuroscience tool for electromagnetic measurements of neurons at the lev...
Neuromorphic studies, which are inspired by the way the human brain works with the extremely low-pow...
This paper presents a CMOS readout circuit for an integrated and highly-sensitive tunnel-magnetores...
Artificial intelligence has become indispensable in modern life, but its energy consumption has beco...
Integrated spintronic biochip platforms are being developed for portable, point-of-care, diagnostic ...
Magnetoencephalography has been established nowadays as a crucial in vivo technique for clinical and...
An alternative neuroscience tool for magnetic field detection is described in this work, providing b...
Spintronic sensors, that are based on the tunnellingmagnetoresistive (TMR) effect, have been utilize...
Magnetism‐based systems are widely utilized for sensing and imaging biological phenomena, for exampl...
In order to measure extremely weak magnetic fields, such as those produced by the neuronal activity ...
Spintronics has gone through substantial progress due to its applications in energy-efficient memory...