The present disclosure is directed to the area of magnetic field measurement systems using one or more optically pumped magnetometers. The present disclosure is also directed to magnetic field measurement systems and methods that include a feedback loop filter to facilitate detection or measurement of low amplitude magnetic fields.
In the nervous system, neurons propagate signals via action potentials. These are brief electric currents which flow down the length of a neuron causing chemical transmitters to be released at a synapse. The time-varying electrical currents within an ensemble of neurons generates a magnetic field, which can be measured using either a Superconductive Quantum Interference Device (SQUID) or an Optically Pumped Magnetometer (OPM). In this disclosure the OPM is primarily considered because the SQUID requires cryogenic cooling, which may make it prohibitively costly for users and too large to be wearable by a user. Magnetoencephalography (MEG), the measurement of magnetic fields generated by the brain, is one application of interest.
One embodiment is a magnetic field measurement system that includes at least one magnetometer having a vapor cell, a light source to direct light through the vapor cell, and a detector to receive light directed through the vapor cell; at least one magnetic field generator disposed adjacent the vapor cell and configured to modify a magnetic field experienced by the vapor cell; and a feedback circuit coupled to the at least one magnetic field generator and the detector of the at least one magnetometer. The feedback circuit includes at least one feedback loop and each of the at least one feedback loop includes a first low pass filter with a first cutoff frequency. The feedback circuit is configured to compensate for magnetic field variations having a frequency lower than the first cutoff frequency using the at least one magnetic field generator. The first low pass filter rejects magnetic field variations having a frequency higher than the first cutoff frequency. The feedback circuit is configured to provide the rejected magnetic field variations for measurement as an output of the feedback circuit.
In at least some embodiments, the first cutoff frequency is in a range of 5 to 40 Hz. In at least some embodiments, the first cutoff frequency is in a range of 8 to 20 Hz.
In at least some embodiments, each of the at least one feedback loop of the feedback circuit includes a proportional integral derivative (PID) element. In at least some embodiments, the first low pass filter is part of the PID element.
In at least some embodiments, at least one of the at least one feedback loop of the feedback circuit further includes a second low pass filter having a second cutoff frequency, wherein the second cutoff frequency is higher than the first cutoff frequency, wherein the feedback circuit is configured to provide magnetic field variations having a frequency between the first cutoff frequency and the second cutoff frequency as the output of the feedback circuit. In at least some embodiments, at least one of the at least one feedback loop of the feedback circuit further includes a modulation source configured to provide modulation at a modulation frequency to a feedback signal generated by the feedback circuit and delivered to the magnetic field generator, wherein the modulation frequency is greater than the second cutoff frequency.
In at least some embodiments, the feedback circuit includes two of the feedback loops. In at least some embodiments, the magnetic field generator includes two pairs of coils, wherein each of the pairs is arranged orthogonal to the other pair and is coupled to one of the two feedback loops.
In at least some embodiments, the feedback circuit includes three of the feedback loops. In at least some embodiments, the magnetometer further includes a pump light source configured to illuminate and pump atoms in the vapor cell. In at least some embodiments, the magnetic field generator includes three pairs of coils, wherein each of the pairs is arranged orthogonal to the other pairs and is coupled to one of the three feedback loops. In at least some embodiments, two of the three feedback loops of the feedback circuit further include a second low pass filter having a second cutoff frequency, wherein the second cutoff frequency is higher than the first cutoff frequency, wherein the feedback circuit is configured to provide magnetic field variations having a frequency between the first cutoff frequency and the second cutoff frequency as the output of the feedback circuit. In at least some embodiments, two of the three feedback loops of the feedback circuit further include a modulation source configured to provide modulation at a modulation frequency to a feedback signal generated by the feedback circuit and delivered to the magnetic field generator, wherein the modulation frequency is greater than the second cutoff frequency.
Another embodiment is a magnetic field measurement system that includes an array of magnetometers, each of the magnetometers including a vapor cell, a light source to direct light through the vapor cell, and a detector to receive light directed through the vapor cell, wherein the array of magnetometers includes a first magnetometer; at least one magnetic field generator, wherein the vapor cell of each of the magnetometers is disposed adjacent at least one of the at least one magnetic field generator which is configured to modify a magnetic field experienced by the vapor cell; and a feedback circuit coupled to each of the at least one magnetic field generator and the detector of the first magnetometer. The feedback circuit includes at least one feedback loop and each of the at least one feedback loop includes a first low pass filter with a first cutoff frequency. The feedback circuit is configured to compensate, in each of the magnetometers, for magnetic field variations having a frequency lower than the first cutoff frequency using the at least one magnetic field generator. The first low pass filter rejects magnetic field variations having a frequency higher than the first cutoff frequency. The feedback circuit is configured to provide the rejected magnetic field variations for measurement as an output of the feedback circuit.
In at least some embodiments, each of the at least one feedback loop of the feedback circuit includes a proportional integral derivative (PID) element. In at least some embodiments, the first low pass filter is part of the PID element.
In at least some embodiments, at least one of the at least one feedback loop of the feedback circuit further includes a second low pass filter having a second cutoff frequency, wherein the second cutoff frequency is higher than the first cutoff frequency, wherein the feedback circuit is configured to provide magnetic field variations having a frequency between the first cutoff frequency and the second cutoff frequency as the output of the feedback circuit.
In at least some embodiments, the feedback circuit includes two of the feedback loops. In at least some embodiments, the feedback circuit includes three of the feedback loops.
Non-limiting and non-exhaustive embodiments of the present invention are described with reference to the following drawings. In the drawings, like reference numerals refer to like parts throughout the various figures unless otherwise specified.
For a better understanding of the present invention, reference will be made to the following Detailed Description, which is to be read in association with the accompanying drawings, wherein:
The present disclosure is directed to the area of magnetic field measurement systems using one or more optically pumped magnetometers. The present disclosure is also directed to magnetic field measurement systems and methods that include a feedback loop filter to facilitate detection or measurement of low amplitude magnetic fields.
Herein the terms “ambient background magnetic field” and “background magnetic field” are interchangeable and used to identify the magnetic field or fields associated with sources other than the magnetic field measurement system and the biological source(s) (for example, neural signals from a user's brain) or other source(s) of interest. The terms can include, for example, the Earth's magnetic field, as well as magnetic fields from magnets, electromagnets, electrical devices, and other signal or field generators in the environment, except for the magnetic field generator(s) that are part of the magnetic field measurement system.
The terms “gas cell”, “vapor cell”, and “vapor gas cell” are used interchangeably herein. Below, a gas cell containing alkali metal vapor is described, but it will be recognized that other gas cells can contain different gases or vapors for operation.
An optically pumped magnetometer (OPM) is a basic component used in optical magnetometry to measure magnetic fields. While there are many types of OPMs, in general magnetometers operate in two modalities: vector mode and scalar mode. In vector mode, the OPM can measure one, two, or all three vector components of the magnetic field; while in scalar mode the OPM can measure the total magnitude of the magnetic field.
Vector mode magnetometers measure a specific component of the magnetic field, such as the radial and tangential components of magnetic fields with respect the scalp of the human head. Vector mode OPMs often operate at zero-field and may utilize a spin exchange relaxation free (SERF) mode to reach femto-Tesla sensitivities. A SERF mode OPM is one example of a vector mode OPM, but other vector mode OPMs can be used at higher magnetic fields. These SERF mode magnetometers can have high sensitivity but may not function in the presence of magnetic fields higher than the linewidth of the magnetic resonance of the atoms of about 10 nT, which is much smaller than the magnetic field strength generated by the Earth. As a result, conventional SERF mode magnetometers often operate inside magnetically shielded rooms that isolate the sensor from ambient magnetic fields including Earth's.
Magnetometers operating in the scalar mode can measure the total magnitude of the magnetic field. (Magnetometers in the vector mode can also be used for magnitude measurements.) Scalar mode OPMs often have lower sensitivity than SERF mode OPMs and are capable of operating in higher magnetic field environments.
The magnetic field measurement systems described herein can be used to measure or observe electromagnetic signals generated by one or more sources (for example, neural signals or other biological sources). The system can measure biologically generated magnetic fields and, at least in some embodiments, can measure biologically generated magnetic fields in an unshielded or partially shielded environment. Aspects of a magnetic field measurement system will be exemplified below using magnetic signals from the brain of a user; however, biological signals from other areas of the body, as well as non-biological signals, can be measured using the system. In at least some embodiments, the system can be a wearable MEG system that can be used outside a magnetically shielded room.
The computing device 150 can be a computer, tablet, mobile device, field programmable gate array (FPGA), microcontroller, or any other suitable device for processing information or instructions. The computing device 150 can be local to the user or can include components that are non-local to the user including one or both of the processor 152 or memory 154 (or portions thereof). For example, in at least some embodiments, the user may operate a terminal that is connected to a non-local computing device. In other embodiments, the memory 154 can be non-local to the user.
The computing device 150 can utilize any suitable processor 152 including one or more hardware processors that may be local to the user or non-local to the user or other components of the computing device. The processor 152 is configured to execute instructions, as described below.
Any suitable memory 154 can be used for the computing device 150. The memory 154 illustrates a type of computer-readable media, namely computer-readable storage media. Computer-readable storage media may include, but is not limited to, volatile, nonvolatile, non-transitory, removable, and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM, digital versatile disks (“DVD”) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computing device.
Communication methods provide another type of computer readable media; namely communication media. Communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, data signal, or other transport mechanism and include any information delivery media. The terms “modulated data signal,” and “carrier-wave signal” includes a signal that has one or more of its characteristics set or changed in such a manner as to encode information, instructions, data, and the like, in the signal. By way of example, communication media includes wired media such as twisted pair, coaxial cable, fiber optics, wave guides, and other wired media and wireless media such as acoustic, RF, infrared, and other wireless media.
The display 156 can be any suitable display device, such as a monitor, screen, or the like, and can include a printer. In some embodiments, the display is optional. In some embodiments, the display 156 may be integrated into a single unit with the computing device 150, such as a tablet, smart phone, or smart watch. In at least some embodiments, the display is not local to the user. The input device 158 can be, for example, a keyboard, mouse, touch screen, track ball, joystick, voice recognition system, or any combination thereof, or the like. In at least some embodiments, the input device is not local to the user.
The magnetic field generator(s) 162 can be, for example, Helmholtz coils, solenoid coils, planar coils, saddle coils, electromagnets, permanent magnets, or any other suitable arrangement for generating a magnetic field. As an example, the magnetic field generator 162 can include three orthogonal sets of coils to generate magnetic fields along three orthogonal axes. Other coil arrangement can also be used. The optional sensor(s) 164 can include, but are not limited to, one or more magnetic field sensors, position sensors, orientation sensors, accelerometers, image recorders, or the like or any combination thereof.
The one or more magnetometers 160 can be any suitable magnetometer including, but not limited to, any suitable optically pumped magnetometer. In at least some embodiments, at least one of the one or more magnetometers (or all of the magnetometers) of the system is arranged for operation in the SERF mode. Examples of magnetic field measurement systems or methods of making such systems or components for such systems are described in U.S. patent application Ser. Nos. 16/213,980; 16/405,382; 16/418,478; 16/418,500; 16/428,871; 16/456,975; 16/457,655; 16/573,394; 16/573,524; 16/679,048; and 16/741,593, and U.S. Provisional Patent Application Ser. Nos. 62/689,696; 62/699,596; 62/719,471; 62/719,475; 62/719,928; 62/723,933; 62/732,327; 62/732,791; 62/741,777; 62/743,343; 62/747,924; 62/745,144; 62/752,067; 62/776,895; 62/781,418; 62/796,958; 62/798,209; 62/798,330; 62/804,539; 62/826,045; 62/827,390; 62/836,421; 62/837,574; 62/837,587; 62/842,818; 62/855,820; 62/858,636; 62/860,001; 62/865,049; 62/873,694; 62/874,887; 62/883,399; 62/883,406; 62/888,858; 62/895,197; 62/896,929; 62/898,461; 62/910,248; 62/913,000; 62/926,032; 62/926,043; 62/933,085; and 62/960,548, all of which are incorporated herein by reference in their entireties.
The light source 172 can include, for example, a laser to, respectively, optically pump the alkali metal atoms and to probe the vapor cell. The light source 172 may also include optics (such as lenses, waveplates, collimators, polarizers, and objects with reflective surfaces) for beam shaping and polarization control and for directing the light from the light source to the cell and detector. Examples of suitable light sources include, but are not limited to, a diode laser (such as a vertical-cavity surface-emitting laser (VCSEL), distributed Bragg reflector laser (DBR), or distributed feedback laser (DFB)), light-emitting diode (LED), lamp, or any other suitable light source. In some embodiments, the light source 172 may include two light sources: a pump light source and a probe light source.
The detector 174 can include, for example, an optical detector to measure the optical properties of the transmitted light field amplitude, phase, or polarization, as quantified through optical absorption and dispersion curves, spectrum, or polarization or the like or any combination thereof. Examples of suitable detectors include, but are not limited to, a photodiode, charge coupled device (CCD) array, CMOS array, camera, photodiode array, single photon avalanche diode (SPAD) array, avalanche photodiode (APD) array, or any other suitable optical sensor array that can measure the change in transmitted light at the optical wavelengths of interest.
These shielded rooms, however, are generally not viable for a consumer market where it is thought that magnetic field measurements systems for MEG should be able to operate in the ambient background magnetic field of the native environment, including the Earth's magnetic field and other local sources of magnetic fields. One additional conventional solution is to incorporate a feedback system to null magnetic fields at the OPM magnetometer operating in the SERF mode. In this arrangement, the current in the feedback coils becomes a measure of the magnetic field. This enables the SERF magnetometer to operate in finite magnetic fields, however it does not address the issue of measuring signals with a dynamic range of 5×109.
In contrast to these conventional arrangements, a new arrangement circumvents the need for such high dynamic range by incorporating a low-pass filter into a feedback loop. Most environmental magnetic field noise and noise due to subject motion occurs at low frequencies (below approximately 10 Hz) and neural signals often occur at higher frequencies (above approximately 50 Hz). The ability of a feedback loop with a low pass filter to track low frequency fluctuations thus reduces the needed dynamic range in the frequency band of interest as the higher amplitude magnetic fields are filtered out due to their low frequency fluctuations. Furthermore, at least some embodiments of the present arrangements can incorporate the same OPM for zero-field finding which may reduce system cost and simplify its use.
In at least some embodiments, the arrangements described herein can enhance the dynamic range of optically pumped magnetometers (OPMs) in magnetic field measurements systems for magnetoencephalography (MEG) to facilitate applications, systems, and arrangements for use outside of magnetically shielded rooms. In at least some embodiments, an arrangement, device, or system as described herein can separate high-frequency neural signals (for example, above a pre-selected or user-defined cutoff frequency) from low frequency noise (in the band from continuous to the pre-selected or user-defined cutoff frequency) arising due to, for example, external field perturbations or user motion in an ambient background magnetic field.
The arrangements and their use and operation will be described herein with respect to the measurement of neural signals arising from signal sources in the brain of a user as an example. It will be understood, however, that these arrangements can be adapted and used to measure other neural signals, other biological signals, or other non-biological signals.
A demodulation and feedback circuit 314 receives the signal from the detector 374 and uses that signal for purposes including, but not limited to, 1) generation of the small magnetic field modulation using the magnetic field generator 362 to convert the vapor cell absorptive resonance (with respect to the magnetic field) into a dispersively shaped error signal in the first harmonic of the demodulated signal, and 2) to implement a feedback loop that can compensate for slowly varying ambient background magnetic field perturbations by running the appropriate quasi-static current through the magnetic field generator 362 to generate a magnetic field near the vapor cell 370.
The demodulation and feedback circuit 314 in
Each feedback loop 316a, 316b also includes a first low pass filter 318a, 318b with a cutoff frequency that passes the slow motions of many background ambient magnetic field variations but excludes the higher frequency neural signals. In the embodiment of
Each feedback loop may also include a second low pass filter 320a, 320b with a cutoff frequency higher than the frequency of the neural signals to be detected. This second low pass filter 320a, 320b may remove higher frequency magnetic field variations, as well as interference from the modulation frequency. The cutoff frequency is selected to be higher than the signals to be detected and may be lower than the modulation frequency. For example, the cutoff frequency can be at least 100, 150, 200, 250 Hz, 500 Hz, or more.
An output 322a, 322b between the low pass filter 320a, 320b and low pass filter 318a, 381b of the PID element provides the neural signal. In at least some embodiments, at the output 322a, 322b, the dispersively shaped error signal from the detector 374, as modified by the demodulation and feedback circuit 314, is linear with respect to the neural signals to be detected.
The arrangement illustrated in
The demodulation and feedback circuit 314 in
Two of the feedback loops 316a, 316b may also include a second low pass filter 320a, 320b with a cutoff frequency higher than the frequency of the neural signals to be detected. This low pass filter 320a, 320b may remove higher frequency magnetic field variations, as well as interference from the modulation frequency. The cutoff frequency is selected to be higher than the signals to be detected and may be lower than the modulation frequency. An output 322a, 322b, 322c prior to the low pass filter 318a, 318b, 318c of the PID element provides the neural signal.
Magnetic field measurement systems involving superconducting quantum interference device magnetometers may also benefit from the feedback loop arrangements presented above.
Another embodiment utilizes more than one magnetometer in an array.
In at least some instances, the embodiments presented above can also be placed inside a shield, such as a wearable passively shielded enclosures or a shielded room, to reduce the ambient background magnetic field.
Examples of magnetic field measurement systems in which the embodiments presented above can be incorporated, and which present features that can be incorporated in the embodiments presented herein, are described in U.S. patent application Ser. Nos. 16/213,980; 16/405,382; 16/418,478; 16/418,500; 16/428,871; 16/456,975; 16/457,655; 16/573,394; 16/573,524; 16/679,048; and 16/741,593, and U.S. Provisional Patent Application Ser. Nos. 62/689,696; 62/699,596; 62/719,471; 62/719,475; 62/719,928; 62/723,933; 62/732,327; 62/732,791; 62/741,777; 62/743,343; 62/747,924; 62/745,144; 62/752,067; 62/776,895; 62/781,418; 62/796,958; 62/798,209; 62/798,330; 62/804,539; 62/826,045; 62/827,390; 62/836,421; 62/837,574; 62/837,587; 62/842,818; 62/855,820; 62/858,636; 62/860,001; 62/865,049; 62/873,694; 62/874,887; 62/883,399; 62/883,406; 62/888,858; 62/895,197; 62/896,929; 62/898,461; 62/910,248; 62/913,000; 62/926,032; 62/926,043; 62/933,085; and 62/960,548, all of which are incorporated herein by reference in their entireties.
In at least some embodiments, a magnetic field measurement system or other system, arrangement, device, or method can incorporate a feedback control loop with a low frequency cut off to correct for user motion/movement without disrupting the recording/detection of neural signals.
In at least some embodiments, the arrangements described herein incorporate a slow feedback loop to suppress low frequency noise in the demodulated magnetometer signal. This enables a SERF magnetometer to operate in finite fields, such as those found outside shielded rooms, which is desirable for commercialization of a wearable device and may reduce the dynamic range to manageable levels for neural signals in a high pass band.
The above specification provides a description of the invention and its manufacture and use. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention also resides in the claims hereinafter appended.
This application claims the benefit of U.S. Provisional Patent Application Ser. No. 62/804,539, filed Feb. 12, 2019, and 62/837,574, filed Apr. 23, 2019, both of which are incorporated herein by reference in their entireties.
Number | Name | Date | Kind |
---|---|---|---|
3173082 | Bell | Mar 1965 | A |
3257608 | Bell | Jun 1966 | A |
3495161 | Bell | Feb 1970 | A |
3501689 | Robbiano | Mar 1970 | A |
3513381 | Happer, Jr. | May 1970 | A |
4193029 | Cioccio | Mar 1980 | A |
4951674 | Zanakis et al. | Aug 1990 | A |
5189368 | Chase | Feb 1993 | A |
5192921 | Chantry et al. | Mar 1993 | A |
5225778 | Chaillout | Jul 1993 | A |
5254947 | Chaillout et al. | Oct 1993 | A |
5309095 | Ahonen et al. | May 1994 | A |
5442289 | Dilorio et al. | Aug 1995 | A |
5444372 | Wikswo, Jr. et al. | Aug 1995 | A |
5471985 | Warden | Dec 1995 | A |
5506200 | Hirschkoff et al. | Apr 1996 | A |
5526811 | Lypchuk | Jun 1996 | A |
5713354 | Warden | Feb 1998 | A |
6144872 | Graetz | Nov 2000 | A |
6339328 | Keene et al. | Jan 2002 | B1 |
6472869 | Upschulte et al. | Oct 2002 | B1 |
6665553 | Kandori et al. | Dec 2003 | B2 |
6806784 | Hollberg et al. | Oct 2004 | B2 |
6831522 | Kitching et al. | Dec 2004 | B2 |
7038450 | Romalis | May 2006 | B2 |
7102451 | Happer et al. | Sep 2006 | B2 |
7145333 | Romalis et al. | Dec 2006 | B2 |
7521928 | Romalis et al. | Apr 2009 | B2 |
7656154 | Kawabata et al. | Feb 2010 | B2 |
7826065 | Okandan et al. | Nov 2010 | B1 |
7872473 | Kitching et al. | Jan 2011 | B2 |
7994783 | Ledbetter et al. | Aug 2011 | B2 |
8054074 | Ishihara et al. | Nov 2011 | B2 |
8212556 | Schwindt et al. | Jul 2012 | B1 |
8258884 | Borwick, III et al. | Sep 2012 | B2 |
8319156 | Borwick, III et al. | Nov 2012 | B2 |
8334690 | Kitching et al. | Dec 2012 | B2 |
8373413 | Sugioka | Feb 2013 | B2 |
8405389 | Sugioka et al. | Mar 2013 | B2 |
8587304 | Budker et al. | Nov 2013 | B2 |
8836327 | French et al. | Sep 2014 | B2 |
8906470 | Overstolz et al. | Dec 2014 | B2 |
8941377 | Mizutani et al. | Jan 2015 | B2 |
9084549 | Desain et al. | Jul 2015 | B2 |
9095266 | Fu | Aug 2015 | B1 |
9116201 | Shah et al. | Aug 2015 | B2 |
9140590 | Waters et al. | Sep 2015 | B2 |
9140657 | Ledbetter et al. | Sep 2015 | B2 |
9169974 | Parsa et al. | Oct 2015 | B2 |
9244137 | Kobayashi et al. | Jan 2016 | B2 |
9291508 | Biedermann et al. | Mar 2016 | B1 |
9343447 | Parsa et al. | May 2016 | B2 |
9366735 | Kawabata et al. | Jun 2016 | B2 |
9383419 | Mizutani et al. | Jul 2016 | B2 |
9395425 | Diamond et al. | Jul 2016 | B2 |
9417293 | Schaffer et al. | Aug 2016 | B2 |
9568565 | Parsa et al. | Feb 2017 | B2 |
9575144 | Kornack et al. | Feb 2017 | B2 |
9601225 | Parsa et al. | Mar 2017 | B2 |
9638768 | Foley et al. | May 2017 | B2 |
9639062 | Dyer et al. | May 2017 | B2 |
9677905 | Waters et al. | Jun 2017 | B2 |
9726626 | Smith et al. | Aug 2017 | B2 |
9726733 | Smith et al. | Aug 2017 | B2 |
9791536 | Alem et al. | Oct 2017 | B1 |
9829544 | Bulatowicz | Nov 2017 | B2 |
9846054 | Waters et al. | Dec 2017 | B2 |
9851418 | Wolf et al. | Dec 2017 | B2 |
9869731 | Hovde et al. | Jan 2018 | B1 |
9915711 | Kornack et al. | Mar 2018 | B2 |
9927501 | Kim et al. | Mar 2018 | B2 |
9948314 | Dyer et al. | Apr 2018 | B2 |
9964609 | Ichihara et al. | May 2018 | B2 |
9964610 | Shah et al. | May 2018 | B2 |
9970999 | Larsen et al. | May 2018 | B2 |
9995800 | Schwindt et al. | Jun 2018 | B1 |
10024929 | Parsa et al. | Jul 2018 | B2 |
10088535 | Shah | Oct 2018 | B1 |
10162016 | Gabrys et al. | Dec 2018 | B2 |
10194865 | Le et al. | Feb 2019 | B2 |
10314508 | Desain et al. | Jun 2019 | B2 |
10371764 | Morales | Aug 2019 | B2 |
20040232912 | Tsukamoto et al. | Nov 2004 | A1 |
20050007118 | Kitching et al. | Jan 2005 | A1 |
20050046851 | Riley, Jr. et al. | Mar 2005 | A1 |
20050206377 | Romalis et al. | Sep 2005 | A1 |
20070076776 | Lust et al. | Apr 2007 | A1 |
20070120563 | Kawabata et al. | May 2007 | A1 |
20070167723 | Park et al. | Jul 2007 | A1 |
20070205767 | Xu et al. | Sep 2007 | A1 |
20090079426 | Anderson | Mar 2009 | A1 |
20090101806 | Masuda | Apr 2009 | A1 |
20100219820 | Skidmore et al. | Sep 2010 | A1 |
20110062956 | Edelstein et al. | Mar 2011 | A1 |
20120112749 | Budker et al. | May 2012 | A1 |
20130082700 | Mizutani et al. | Apr 2013 | A1 |
20130082701 | Mizutani et al. | Apr 2013 | A1 |
20130265042 | Kawabata et al. | Oct 2013 | A1 |
20140121491 | Zhang | May 2014 | A1 |
20140306700 | Kamada et al. | Oct 2014 | A1 |
20140354275 | Sheng et al. | Dec 2014 | A1 |
20150022200 | Ichihara et al. | Jan 2015 | A1 |
20150054504 | Ichihara et al. | Feb 2015 | A1 |
20150219732 | Diamond | Aug 2015 | A1 |
20150378316 | Parsa et al. | Dec 2015 | A1 |
20160061913 | Kobayashi et al. | Mar 2016 | A1 |
20160116553 | Kim | Apr 2016 | A1 |
20160223627 | Shah et al. | Aug 2016 | A1 |
20160291099 | Ueno | Oct 2016 | A1 |
20160313417 | Kawabata et al. | Oct 2016 | A1 |
20170023653 | Kobayashi et al. | Jan 2017 | A1 |
20170023654 | Kobayashi et al. | Jan 2017 | A1 |
20170067969 | Butters | Mar 2017 | A1 |
20170199138 | Parsa et al. | Jul 2017 | A1 |
20170199251 | Fujii et al. | Jul 2017 | A1 |
20170261564 | Gabrys et al. | Sep 2017 | A1 |
20170331485 | Gobet et al. | Nov 2017 | A1 |
20170343617 | Manickam et al. | Nov 2017 | A1 |
20170343695 | Stetson et al. | Nov 2017 | A1 |
20170356969 | Ueno | Dec 2017 | A1 |
20180003777 | Sorensen et al. | Jan 2018 | A1 |
20180038921 | Parsa et al. | Feb 2018 | A1 |
20180100749 | Waters et al. | Apr 2018 | A1 |
20180128885 | Parsa et al. | May 2018 | A1 |
20180156875 | Herbsommer et al. | Jun 2018 | A1 |
20180219353 | Shah | Aug 2018 | A1 |
20180238974 | Shah et al. | Aug 2018 | A1 |
20180313908 | Knappe et al. | Nov 2018 | A1 |
20180313913 | DeNatale et al. | Nov 2018 | A1 |
20190391213 | Alford | Dec 2019 | A1 |
20200025844 | Alford et al. | Jan 2020 | A1 |
20200057115 | Jiménez-Martínez et al. | Feb 2020 | A1 |
20200057116 | Zorzos et al. | Feb 2020 | A1 |
20200072916 | Alford et al. | Mar 2020 | A1 |
20200088811 | Mohseni | Mar 2020 | A1 |
20200241094 | Alford | Jul 2020 | A1 |
20200256929 | Ledbetter et al. | Aug 2020 | A1 |
20200309873 | Ledbetter et al. | Oct 2020 | A1 |
20200334559 | Anderson et al. | Oct 2020 | A1 |
20200341081 | Mohseni et al. | Oct 2020 | A1 |
20200381128 | Pratt et al. | Dec 2020 | A1 |
20200400763 | Pratt | Dec 2020 | A1 |
Number | Date | Country |
---|---|---|
10730484 | Jun 2015 | CN |
107562188 | Jan 2018 | CN |
2738627 | Jun 2014 | EP |
2380029 | Oct 2015 | EP |
3037836 | Sep 2017 | EP |
2016109665 | Jun 2016 | JP |
2018004462 | Jan 2018 | JP |
2005081794 | Sep 2005 | WO |
2014031985 | Feb 2014 | WO |
2017095998 | Jun 2017 | WO |
Entry |
---|
Tierney, T.M., Holmes, N., Meyer, S.S., Boto, E., Roberts, G., Leggett, J., . . . Barnes, G. R. (2018). Cognitive neuroscience using wearable magnetometer arrays: Non-invasive assessment of language function. NeuroImage, 181, 513-520. |
Boto, E, Holmes, N, Leggett, J, Roberts, G, Shah, V, Meyer, SS, Munoz, LD, Mullinger, KJ, Tierney, TM, Bestmann, S, Barnes, GR, Bowtell, R & Brookes, MJ 2018, ‘Moving magnetoencephalography towards real world applications with a wearable system’, Nature, vol. 555, pp. 657-661. |
Ijsselsteijn, R & Kielpinski, Mark & Woetzel, S & Scholtes, Theo & Kessler, Ernst & Stolz, Ronny & Schultze, V & Meyer, H-G. (2012). A full optically operated magnetometer array: An experimental study. The Review of scientific instruments. 83. 113106. 10.1063/1.4766961. |
International Search Report and Written Opinion for PCT/US2020/015055 dated May 15, 2020. |
Allred, J.C., Lyman, R. N., Kornack, T. W., & Romalis, M. V. (2002). Hight-sensitivity atomic magnetometer unaffected by spin-exchange relaxation. Physical review letters, 89(13), 130801. |
Balabas et al. Polarized alkali vapor with minute-long transverse spin-relaxation time, Phys. Rev. Lett. 105, 070801—Published Aug. 12, 2010. |
Barbieri, F., Trauchessec, V., Caruso, L., Trejo-Rosillo, J., Talenczuk, B., Paul, E., . . . & Ouanounou, G. (2016), Local recording of biological magnetic fields using Giant Magneto Resistance-based micro-probes. Scientific reports, 6, 39330. |
Dmitry Budker and Michael Romalis, “Optical Magnetometry,” Nature Physics, 2008, https://arxiv.org/abs/physics/0611246v1. |
Anthony P. Colombo, Tony R. Carter, Amir Borna, Yuan-Yu Jau, Cort N. Johnson, Amber L. Dagel, and Peter D. D. Schwindt, “Four-channel optically pumped atomic magnetometer for magnetoenephalography,” Opt. Express 24, 15403-15416 (2016). |
Dang, H.B. & Maloof, A.C. & Romalis, Michael. (2009). Ultra-high sensitivity magnetic field and magnetization measurement with an atomic magnetometer. Applied Physics Letters. 97. 10.1063/1.3491215. |
Donley, E.A. & Hodby, E & Hollberg, L & Kitching, J. (2007). Demonstration of high-performance compact magnetic shields for chip-scale atomic devices. The Review of scientific instruments. 78. 083102. |
Hämäläinen, Matti & Hari, Riitta & Ilmoniemi, Risto J. & Knuutila, Jukka & Lounasmaa, Olli V. Apr. 1993. Magnetoencephalograph—theory, instrumentation, and applications to noninvasive studies of the working human brain. Reviews of Modern Physics. vol 65, Issue 2. 413-497. |
Hunter, D. and Piccolomo, S. and Pritchard, J. D. and Brockie, N. L. and Dyer, T. E. and Riis, E. (2018) Free-induction-decay magnetometer based on a mircrofabricated Cs vapor cell. Physical Review Applied (10).ISSN 2331-7019. |
Jiménez-Martinez, R., Griffith, W. C., Wang, Y. J., Knappe, S., Kitching, J., Smith, K., & Prouty, M. D. (2010). Sensitivity comparison of Mx and frequency-modulated bell—bloom Cs magnetometers in a microfabricated cell. IEEE Transactions on Instruments and Measurement, 59(2), 372-378. |
Kiwoong Kim, Samo Begus, Hui Xia, Seung-Kyun Lee, Vojko Jazbinsek, Zconko Trontelj, Michael V. Romalis, Multi-channel atomic magnetometer for magnetoencephalography: A configuration study. NeuroImage 89 (2014) 143-151 http://physics.princeton.edu/romalis/papers/Kim_2014.pdf. |
Knappe, Svenja & Sander, Tilmann & Trahms, Lutz. (2012). Optically-Pumped Magnetometers for MEG Magnetoencephalography: From Signals to Dynamics Cortical Networks. 993-999. 10.1007/978-3-642-33045-2_49. |
Kominis, I.K., Kornack, T.W., Allred, J.C. and Romalis, M.V., 2003. A subfemtotesla multichannel atomic magnetometer. Nature, 422(6932), p. 596. |
Korth, H., K. Strohbehn, F. Tejada, A. G. Andreou, J. Kitching, S. Knappe, S. J. Lehtonen, S. M. London, and M. Kafel (2016), Miniature atomic scalarmagnetometer for space based on the rubidium isotope 87Rb, J. Geophys. Res. Space Physics, 121, 7870-7880, doi: 10.1002/2016JA022389. |
Lenz, J. and Edelstein, S., 2006. Magnetic sensors and their applications. IEEE Sensors journal, 6(3), pp,631-649. |
Li, S & Vachaspati, Pranjal & Sheng, Dehong & Dural, Nezih & Romalis, Michael. (2011). Optical rotation in excess of 100 rad generated by Rb vapor in a multipass cell. Phys. Rev. A. 84, 10.1103/PhysRevA.84.061403. |
Maze, J. R., Stanwix, P. L., Hodges, J. S., Hong, S., Taylor, J. M., Cappellaro, P., . . . & Yacoby, A. (2008). Nanoscale magnetic sensing with an individual electronic spin in diamond. Nature, 455(7213), 644. |
Sander TH, Preusser J, Mhaskar R, Kitching J, Trahms L, Knappe S. Magnetoencephalography with a chip-scale atomic magnetometer. Biomed Opt Express. 2012;3(5):981-90. |
J. Seltzer, S & Romalis, Michael. (2010). High-temperature alkali vapor cells with antirelaxation surface coatings. Journal of Applied Physics. 106. 114905-114905. 10.1063/1.3236649. |
Seltzer, S. J., and Romalis, M.V., “Unshielded three-axis vector operation of a spin-exchange-relaxation-free atomic magnetometer.” Applied physics letters 85.20 (2004): 4804-4806. |
Sheng, Dong & R. Perry, Abigail & Krzyzewski, Sean & Geller, Shawn & Kitching, John & Knappe, Svenja. (2017). A microfabricated optically-pumped magnetic gradiometer. Applied Physics Letters. 110. 10.1063/1.4974349. |
Sheng, Dehong & Li, S & Dural, Nezih & Romalis, Michael. (2013). Subfemtotesla Scalar Atomic Magnetometry Using Multipass Cells. Physical review letters. 110. 160802. 10.1103/PhysRevLett. 110.160802. |
Volkmar Schultze et al. An Optically Pumped Magnetometer Working in the Light-Shift Dispersed Mz Mode, Sensors 2017, 17, 561; doi:10.3390/s17030561. |
Fang, J. and Qin, J., 2012. In situ triaxial magnetic field compensation for the spin-exchange-relaxation-free atomic magnetometer. Review of Scientific Instruments, 83(10), p. 103104. |
Joon Lee, Hyun & Shim, Jeong & Moon, Han Seb & Kim, Kiwoong. (2014). Flat-response spin-exchange relaxation free atomic magnetometer under negative feedback. Optics Express. 22. 10.1364/OE.22.019887. |
Griffith, Clark & Jimenez-Martinez, Ricardo & Shah, Vishal & Knappe, Svenja & Kitching, John. (2009). Miniature atomic magnetometer integrated with flux concentrators. Applied Physics Letters—Appl Phys Lett. 94. 10. 1063/1.3056152. |
Lee, S.-K & Romalis, Michael. (2008). Calculation of Magnetic Field Noise from High-Permeability Magnetic Shields and Conducting Objects with Simple Geometry. Journal of Applied Physics. 103. 084904-084904. 10.1063/1.2885711. |
Vovrosh, Jamie & Voulazeris, Georgios & Petrov, Plamen & Zou, Ji & Gaber Beshay, Youssef & Benn, Laura & Woolger, David & Attallah, Moataz & & Boyer, Vincent & Bongs, Kai & Holynski, Michael. (2018). Additive manufacturing of magnetic shielding and ultra-high vacuum flange for cold atom sensors. Scientific Reports. 8. 10.1038/s41598-017-20352-x. |
Kim, Young Jin & Savukov, I. (2016). Ultra-sensitiive Magnetic Microscopy with an Optically Pumped Magnetometer. Scientifiic Reports. 6. 24773. 10.1038/srep24773. |
Navau, Caries & Prat-Camps, Jordi & Sanchez, Alvaro. (2012). Magnetic Energy Harvesting and Concentration at a Distance by Transformation Optics. Physical review letters. 109. 263903. 10.1103/PhysRevLett.109.263903. |
Orang Alem, Rahul Mhaskar, Ricardo Jiménez-Martínez, Dong Sheng, John LeBlanc, Lutz Trahms, Tilmann Sander, John Kitching, and Svenja Knappe, “Magnetic field imaging with microfabricated optically-pumped magnetometers,” Opt. Express 25, 7849-7858 (2017). |
Slocum et al., Self-Calibrating Vector Magnetometer for Space, https://esto.nasa.gov/conferences/estc-2002/Papers/B3P4(Slocum).pdf. |
Dupont-Roc, J & Haroche, S & Cohen-Tannoudji, C. (1969). Detection of very weak magnetic fields (10-9gauss) by 87Rb zero-field level crossing resonances. Physics Letters A—Phys Lett A. 28. 638-639. 10.1016/0375-9601(69) 90480-0. |
J. A. Neuman, P. Wang, and A. Gallagher, Robust high-temperature sapphire cell for metal vapors, Review of Scientific Instruments, vol. 66, Issue 4, Apr. 1995, pp. 3021-3023. |
Borna, Amir, et al. “A 20-channel magnetoencephalography system based on optically pumped magnetometers.” Physics in Medicine & Biology 62 .23 (2017): 8909. |
R. E. Slocum & L. J. Ryan, Design and operation of the minature vector laser magnetometer, Nasa Earth Science Technology Conference 2003. |
Schoenmaker, Jeroen & R Pirota, K & Teixeira, Julio. (2013). Magnetic flux amplification by Lenz lenses. The Review of scientific instruments. 84. 085120. 10.1063/1.4819234. |
Hu, Yanhui & Hu, Zhaohui & Liu, Xuejing & Li, Yang & Zhang, Ji & Yao, Han & Ding, Ming. (2017). Reduction of far off-resonance laser frequency drifts based on the second harmonic of electro-optic modulator detection in the optically pumped magnetometer. Applied Optics. 56. 5927. 10.1364/AO.56.005927. |
Masuda, Y & Ino, T & Skoy, Vadim & Jones, G.L. (2005). 3He polarization via optical pumping in a birefringent cell. Applied Physics Letters. 87. 10.1063/1.2008370. |
A.B. Baranga et al., An atomic magnetometer for brain activity imaging, Real Time Conference 2005. 14th IEEE-NPSS. pp. 417-418. |
Larry J, Ryan, Robert E. Slocum, and Robert B. Steves, Miniature Vector Laser Magnetometer Measurements of Earth's Field, May 10, 2004, 4 pgs. |
Lorenz, V. O., Dai, X., Green, H., Asnicar, T. R., & Cundiff, S. T. (2008). High-density, high-temperature alkali vapor cell. Review of Scientific Instruments, 78(12), 4 pages. |
F. Jackson Kimball, D & Dudley, J & Li, Y & Thulasi, Swencha & Pustelny, Szymon & Budker, Dmitry & Zolotorev, Max. (2016). Magnetic shielding and exotic spin-dependent interactions. Physical Review D. 94. 10.1103/PhysRevD.94.082005. |
Huang, Haichao, et al. “Single-beam three-axis magnetometer.” Applied Physics Letters 109.6 (2016): 062404. (Year: 2016). |
Scott Jeffrey Seltzer: “Developments in alkali-metal atomic magnetometry”, Nov. 1, 2008 (Nov. 1, 2008), XP055616618, ISBN: 978-0-549-933355-7 Retrieved from the Internet: URL:http://physics.princeton.edu/atomic/romalis/papers/Seltzer%20Thesis.pdf [retrieved on Aug. 29, 2019] pp. 148-159. |
Haifeng Dong et al: “Atomic-Signal-Based Zero-Field Finding Technique for Unshielded Atomic Vector Magnetometer”, IEEE Sensors Journal, IEEE Service Center, New York, NY, US vol. 13, No. 1, Jan. 1, 2013 (Jan. 1, 2013), pp. 186-189. |
Arjen Stolk, Ana Todorovic, Jan-Mathijs Schoffelen, and Robert Oostenveld. “Online and offline tools for head movement compensation in MEG.” Neuroimage 68 (2013): 39-48. |
Bagherzadeh, Yasaman, Daniel Baldauf, Dimitrios Pantazis, and Robert Desimone. “Alpha synchrony and the neurofeedback control of spatial attention.” Neuron 105, No. 3 (2020): 577-587. |
Hill RM, Boto E, Holmes N, et al. A tool for functional brain imaging with lifespan compliance [published correction appears in Nat Commun. Dec. 4, 2019;10(1):5628]. Nat Commun. 2019;10(1):4785. Published Nov. 5, 2019. doi:10.1038/s41467-019-12486-x. |
Zetter, R., Iivanainen, J. & Parkkonen, L. Optical Co-registration of MRI and On-scalp MEG. Sci Rep 9, 5490 (2019). https://doi.org/10.1038/s41598-019-41763-4. |
Garrido-Jurado, Sergio, Rafael Muñoz-Salinas, Francisco José Madrid-Cuevas and Manuel J. Marín-Jiménez. “Automatic generation and detection of highly reliable fiducial markers under occlusion.” Pattern Recognit. 47 (2014): 2280-2292. |
Hill RM, Boto E, Rea M, et al. Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system [published online ahead of print, May 29, 2020]. Neuroimage. 2020;219:116995. doi:10.1016/j.neuroimage.2020.116995. |
V. Kazemi and J. Sullivan, “One millisecond face alignment with an ensemble of regression trees,” 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, 2014, pp. 1867-1874, doi: 10.1109/CVPR.2014.241. |
Holmes, N., Tierney, T.M., Leggett, J. et al. Balanced, bi-planar magnetic field and field gradient coils for field compensation in wearable magnetoencephalography. Sci Rep 9, 14196 (2019). |
N. Holmes, J. Leggett, E. Boto, G. Roberts, R.M. Hill, T.M. Tierney, V. Shah, G.R. Barnes, M.J. Brookes, R. Bowtell A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography Neuroimage, 181 (2018), pp. 760-774. |
J. M. Leger et. al., In-flight performance of the Absolute Scalar Magnetometer vector mode on board the Swarm satellites, Earth, Planets, and Space (2015) 67:57. |
Alexandrov, E. B., Balabas, M. V., Kulyasov, V. N., Ivanov, A. E., Pazgalev, A. S., Rasson, J. L., . . . (2004). Three-component variometer based on a scalar potassium sensor. Measurement Science and Technology, 15(5), 918-922. |
Gravrand, O., Khokhlov, A., & JL, L. M. (2001). On the calibration of a vectorial 4He pumped magnetometer. Earth, planets and space , 53 (10), 949-958. |
Boma, Amir & Carter, Tony & Colombo, Anthony & Jau, Y-Y & McKay, Jim & Weisend, Michael & Taulu, Samu & Stephen, Julia & Schwindt, Peter. (2018). Non-Invasive Functional-Brain-Imaging with a Novel Magnetoencephalography System. 9 Pages. |
Vrba J, Robinson SE. Signal processing in magnetoencephalography. Methods. 2001;25(2):249-271. doi:10.1006/meth.2001.1238. |
Jusitalo M and Ilmoniemi R., 1997, Signal-space projection method for separating MEG or EEG into components. Med. Biol. Comput. (35) 135-140. |
Taulu S and Kajola M., 2005, Presentation of electromagnetic multichannel data: the signal space separation method. J. Appl. Phys. (97) 124905 (2005). |
Taulu S, Simola J and Kajola M., 2005, Applications of the signal space separation method. IEEE Trans. Signal Process. (53) 3359-3372 (2005). |
Taulu S, Simola J., 2006, Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Phys. Med. Biol. (51) 1759-1768 (2006). |
Johnson, et al., Magnetoencephalography with a two-color pump-probe, fiber-coupled atomic magnetometer, Applied Physics Letters 97, 243703 2010. |
Zhang, et al., Magnetoencephalography using a compact multichannel atomic magnetometer with pump-probe configuration, AIP Advances 8, 125028 (2018). |
Xia, H. & Ben-Amar Baranga, Andrei & Hoffman, D. & Romalis, Michael. (2006). Magnetoencephalography with an atomic magnetometer. Applied Physics Letters—Appl Phys Lett. 89. 10.1063/1.2392722. |
Ilmoniemi, R. (2009). The triangle phantom in magnetoencephalography. In 24th Annual Meeting of Japan Biomagnetism and Bioelecctromagnetics Society, Kanazawa, Japan, 28.29.5.2009 (pp. 6263). |
Oyama D. Dry phantom for magnetoencephalography—Configuration, calibration, and contribution. J Neurosci Methods. 2015;251:24-36. doi: 0.1016/j.jneumeth.2015.05.004. |
Chutani, R., Maurice, V., Passilly, N. et al. Laser light routing in an elongated micromachined vapor cell with diffraction gratings for atomic clock applications. Sci Rep 5, 14001 (2015). https://doi.org/10.1038/srep14001. |
Eklund, E. Jesper, Andrei M. Shkel, Svenja Knappe, Elizabeth A. Donley and John Kitching. “Glass-blown spherical microcells for chip-scale atomic devices.” (2008). |
Jiménez-Martínez R, Kennedy DJ, Rosenbluh M. et al. Optical hyperpolarization and NMR detection of 129Xe on a microfluidic chip. Nat Commun. 2014;5:3908. Published May 20, 2014. doi:10.1038/ncomms4908. |
Boto, Elena, Sofie S. Meyer, Vishal Shah, Orang Alem, Svenja Knappe, Peter Kruger, T. Mark Fromhold, et al. “A New Generation of Magnetoencephalography: Room Temperature Measurements Using Optically-Pumped Magnetometers.” NeuroImage 149 (Apr. 1, 2017): 404-14. |
Bruno, A. C., and P. Costa Ribeiro. “Spatial Fourier Calibration Method for Multichannel Squid Magnetometers.” Review of Scientific Instruments 62, No. 4 (Apr. 1, 1991): 1005-9. |
Chella, Federico, Filippo Zappasodi, Laura Marzetti, Stefania Della Penna, and Vittorio Pizzella. “Calibration of a Multichannel MEG System Based on the Signal Space Separation Method.” Physics in Medicine and Biology 57 (Jul. 13, 2012): 4855-70. |
Pasquarelli, A, M De Melis, Laura Marzetti, Hans-Peter Müller, and S N Emé. “Calibration of a Vector-MEG Helmet System.” Neurology & Clinical Neurophysiology□: NCN 2004 (Feb. 1, 2004): 94. |
Pfeiffer, Christoph, Lau M. Andersen, Daniel Lundqvist, Matti Hämäläinen, Justin F. Schneiderman, and Robert Oostenveld. “Localizing On-Scalp MEH Sensors Using an Array of Magnetic Dipole Coils.” PLOS ONE 13, No. 5 (May 10, 2018): e0191111. |
Vivaldi, Valentina, Sara Sommariva, and Alberto Sorrentino. “A Simplex Method for the Calibration of a MEG Device.” Communications in Applied and Industrial Mathematics 10 (Jan. 1, 2019): 35-46. |
Nagel, S., & Spüler, M. (2019). Asynchronous non-invasive high-speed BCI speller with robust non-control state detection. Scientific Reports, 9(1), 8269. |
Thielen, J., van den Broek, P., Farquhar, J., & Desain, P. (2015). Broad-Band Visually Evoked Potentials: Re(con) volution in Brain-Computer Interfacing. PloS One, 10(7), e0133797. https://doi.org/10.1371/journal.pone.0133797. |
J. Kitching, “Chip-scale atomic devices,” Appl. Phys. Rev. 5(3), 031302 (2018), 39 pages. |
Manon Kok, Jeroen D. Hol and Thomas B. Schon (2017), “Using Inertial Sensors for Position and Orientation Estimation”, Foundations and Trends in Signal Processing: vol. 11: No. 1-2, pp. 1-153. http://dx.doi.org/10.1561/2000000094. |
Number | Date | Country | |
---|---|---|---|
20200256929 A1 | Aug 2020 | US |
Number | Date | Country | |
---|---|---|---|
62837574 | Apr 2019 | US | |
62804539 | Feb 2019 | US |