DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Claim Rejections - 35 USC § 102/103
Applicant’s arguments, filed 05/18/2026, with respect to the rejection(s) of claim(s) 1-14 under 35 USC 102/102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Sullivan (US 20100234752 A1 – hereinafter Sullivan) in view of Alailima (US 20200114115 A1 – hereinafter Alailima)
Claim Rejections - 35 USC § 101
Applicant's arguments filed 05/18/2026 have been fully considered but they are not persuasive.
Step 2A, prong 1: Applicant argues that cannot mentally generate sensory stimulation signals and detect evoked potentials. Examiner emphasizes that the claims are directed to mental processes directed to the underlined detecting the evoked potentials and selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals. A human cannot generate sensory stimulation signals; however, Examiner did not underline this portion of the claim to encompass a mental process. For claims 1 and 11, it is reasonable to interpret that a person could mentally detect something by simple observation and identification, for example by simply observing and identifying when an EEG signal is detected by an EEG detection device. Under the broadest reasonable interpretation of the claim, detecting EEG signals requires no more than mere observation and evaluation of received EEG data via a detection device or user interface, or in the instant case, detecting an evoked potential simply by looking at signal data. A person could then mentally select frequencies by mentally identifying and choosing which frequencies to use. Therefore, claims 1 and 11 are directed to mental processes, but for the recitation of well-understood, routine and conventional elements.
Step 2A, prong 2 and 2B: Applicant argues technological improvement over Brain-Computer Interfaces. Examiner respectfully argues that the claims are ultimately directed to mental processes (i.e. detecting, selecting), and therefore cannot be considered technological improvements. Specifically, the claims include generic additional elements (memory, processor, signal generator, human-machine interface), which is merely considered generally linking the use of the mental processes to a particular technological environment or field of use, and does not amount to significantly more than the exception itself, and cannot be considered integrating a judicial exception into a practical application not technological improvement, see MPEP 2106.05(h). In other words, mere automation of manual processes, or mental processes in this case, using well-understood, routine and conventional elements is not considered to be an improvement to technology, but is only directed to mental processes themselves. Therefore, claims 1 and 11 are not considered to be tied to improvements to technology and/or technological environment, but only to judicial exceptions without significantly more, specifically to mental processes but for the recitation of generic well-understood, routine and conventional elements. Claims 1-11 stand rejected under 35 USC 101.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. FR2111859, filed on 11/09/2021.
Information Disclosure Statement
The information disclosure statement(s) filed 05/09/2024, 07/18/2024, and 12/20/2024 has/have been considered by the Examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter (abstract ideas) without significantly more.
The framework for establishing a prima facie case of lack of subject matter eligibility requires that the Examiner determine: (1) Does the claim fall within the four categories of patent eligible subject matter; (2a) prong 1: Does the claim recite an abstract idea, law of nature, or natural phenomenon and (2a) prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application; and (2b) Does the claim recite additional elements that amount of significantly more than the judicial exception.
Step 1):
Claims 1-10 recite a method, which satisfies the 4 statutory categories (process, machine, manufacture, or composition of matter) of patent-eligible subject matter.
Claims 11 recite a non-transitory computer readable medium, which satisfies the 4 statutory categories (process, machine, manufacture, or composition of matter) of patent-eligible subject matter.
Step 2a) Prong One:
Independent claim 1 recites:
A detection method for implemented by a device and comprising:
generating sensory stimulation signals to be applied to a user by a human-machine interface intended for the user, the sensory stimulation signals being periodic and adjustable in frequency;
detecting evoked potentials in physiological signal (EEG) signals of the user as respective reactions to the generating of the sensory stimulation signals; and
selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals.
Independent claim 11 recites:
A non-transitory computer readable medium comprising instruction stored thereon for implementing a method for detecting evoked potentials in a physiological signal of the user, when said instructions are executed by a processor of a processing circuit, wherein the method comprises:
generating sensory stimulation signals to be applied by a human machine interface intended for the user, the sensory stimulation signals being periodic and adjustable in frequency;
detecting the evoked potentials in the physiological signals of the user, in reaction to the generating of the sensory stimulation signals; and
selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals.
Independent claims 1 and 11 are all directed to MENTAL PROCESSES, where nothing in the claim elements precludes the steps from practically being performed in the human mind but for the recitation of generic computer parts or by a human using pen and paper. In the instant case, a person could mentally detect by simple observation and identification. A person could then select by mentally identifying and choosing.
Dependent claims 2-10 contain no additional elements that integrate the abstract ideas into practical application, or amount to significantly more than the abstract idea itself. Dependent claims 2-6 and 10 are all further directed to mental processes (i.e. detecting, adjusting, selecting, storing). Dependent claims 2-10 only further define the abstract ideas (mental processes) in determining first pacing rates and receiving first blood pressures, and do not amount to significantly more than the abstract idea itself. Accordingly, the dependent claims are also directed to non-statutory subject matter.
Step 2a) Prong Two:
This judicial exception is not integrated into a practical application because mere instruction to implement on a computer, or merely using a computer as a tool to perform the abstract idea, adding insignificant extra solution activity, and/or generally linking the use of the abstract idea to a technological environment or field of use is not considered integration into a practical application. The Court defines the phrase “integration into a practical application” to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
This judicial exception is not integrated into a practical application because claims 1-11 do not disclose using the result of the mental process steps (i.e. receiving and determining), for prophylactic treatment of a particular medical condition under MPEP 2106.05(e). In the instant case, there is no specific treatment in the form of stimulation/pacing pulses, drug therapy, radiation therapy, or other forms of treatment that is ultimately used to treat a particular condition as a result of the mental process steps (i.e. detecting, selecting). There is no specific treatment delivered to treat a particular condition that is specified in the claims, but is only directed to abstract ideas (mental processes) as stated above, of which can be performed by a human but for the recitation of generic computers, or with pen and paper. Accordingly, claims 1-11 do not disclose using the result of the mental processes steps for prophylactic treatment of a particular medical condition under MPEP 2106.05(e).
This judicial exception is not integrated into a practical application because claims 1-11 do not provide improvements to the functioning of a computer or to any the technical field under MPEP 2106.05(a). Specifically, the claims recite generic computer elements (processor, generator, human-machine interface), but these elements have not been described with sufficient detail to constitute an improvement in the tech field, as such these features merely define the field of use for the current invention by generally linking mental processes to generic computer elements as a tool to execute the abstract ideas (mental processes). By failing to explain how these elements are different from conventional computer elements, it is reasonable that the broadest reasonable interpretation of the additional elements is just a conventional computer performing generic functions (e.g., data analysis). Conventional computer elements performing basic data analysis is directed to the components of a system amounting to merely field of use type limitations and/or extra solution activity to implement the abstract idea as identified above, and merely including instructions to implement abstract ideas on a computer does not integrate the judicial exception into practical application, see MPEP 2106.04(d) Integration of a Judicial Exception into a Practical Application.
Additional elements further include steps of “generating sensory stimulation signals…”, of which can be considered pre-solution activity as a data-gathering step by administering stimulation signals to obtain evoked potential data. As such, these additional elements are merely nominal or tangential additions to the claims as they do not impose any meaningful limits on the claim, see MPEP 2106.05(g) Insignificant Extra-Solution Activity.
Accordingly, dependent claims 2-10 do not recite additional elements which practically integrate the judicial exception(s) of the current invention.
Step 2b)
Step 2B in the analysis requires us to determine whether the claims do significantly more than
simply describe that abstract method. Mayo, 132 S. Ct. at 1297. We must examine the limitations of the
claims to determine whether the claims contain an "inventive concept" to "transform" the claimed
abstract idea into patent-eligible subject matter. Alice, 134 S. Ct. at 2357 (quoting Mayo, 132 S. Ct. at
1294, 1298). The transformation of an abstract idea into patent-eligible subject matter "requires 'more
than simply stat[ing] the [abstract idea] while adding the words 'apply it."' Id. (quoting Mayo, 132 S. Ct.
at 1294) (alterations in original). "A claim that recites an abstract idea must include 'additional features'
to ensure 'that the [claim] is more than a drafting effort designed to monopolize the [abstract idea].'" Id.
(quoting Mayo, 132 S. Ct. at 1297) (alterations in original). Those "additional features" must be more
than "well-understood, routine, conventional activity." Mayo, 132 S. Ct. at 1298.
The claims also do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements as stated above is/are recognized as generic computer interfaces and generic computers (or computer components), because the claims do not describe these features as having distinguishing element(s) over their generic counterparts, which are well-understood, routine and conventional activities previously known in the industry, as shown in the reference as taught by Sullivan (US 20100234752 A1) used in the rejection below, which teaches a detection system (paragraph 0005), comprising a human-machine interface (figures 7-8), sensory signal generator (paragraph 0026, paragraph 0040 – “…a controller 620 for controlling LED (flashing) lights system 650…”), memory and processor (paragraph 0021).
Additionally, Sabel (US 20090319004 A1) similarly teaches a detection system (abstract) comprising a human-machine interface (figure 2), sensory stimulus generator (figure 2, sense stimulation signal generator 9) which delivers varying frequency of the sensory stimulus signal (paragraph 0017), and includes memory (paragraph 0023 and figure 2, memory unit 16) and processing units (control unit 12, figure 2).
Thus, the present claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. When looked at individually and as a whole, the claim limitations are determined to be an abstract idea without significantly more, and thus claims 1-11 are not patent eligible under 35 USC § 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1 and 8-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan (US 20100234752 A1 – hereinafter Sullivan) in view of Alailima (US 20200114115 A1 – hereinafter Alailima).
Re. claim 1, Sullivan teaches detection method implemented by a device (abstract – “An EEG control of devices using Sensory Evoked Potentials (SEPs) (e.g., visually-evoked potentials), is disclosed”) and comprising:
generating, by a signal generator of the device, sensory stimulation signals to be applied to a user (paragraph 0026 – “In some embodiments, a system is provided that uses flashing lights (e.g., from one or more light-emitting diodes (LEDs) and/or from a computer screen or television (TV) screen) that correspond to commands to/from a user… As used herein, SEPs generally refer to involuntary EEG signals generated when the user is exposed to (e.g., rapidly) repeating sensory stimuli (e.g., visual, such as a flashing light or another involuntary response to a visual stimulus event, audio, tactile, or other stimulus event)”) by a human machine interface intended for the user (figures 7-8),
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the sensory stimulation signals being periodic (paragraph 0026 – “In some embodiments, the flashing lights in the system flash at variable frequencies in a fixed pattern or in non-periodic frequencies”),
and adjustable in frequency (paragraph 0030 – “In some embodiments, various parameters are adjusted to maximize the EEG signal and increase the visually-evoked potential detection rate, such as light brightness, color, spacing, frequency…”; paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”);
and detecting evoked potentials in physiological signals of the user received by an input interface of the device, as respective reactions to the generating of the sensory stimulation signals (paragraph 0030 – “In some embodiments, various parameters are adjusted to maximize the EEG signal and increase the visually-evoked potential detection rate, such as light brightness, color, spacing, frequency, duty cycle, and the amount of visual field that is used by the lights. When a visually-evoked potential is detected, then the corresponding command is sent to the controlled device”; paragraph 0033 – “In some embodiments, the EEG detection system 130 detects EEG signals of a user, and the EEG control system 110 includes a processor configured to perform an SEP [Sensory Evoked Potentials] determination algorithm (e.g., a real-time classification algorithm/classifier) for EEG signals detected by EEG detection system 130”).
Sullivan does not expressly teach selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals.
Alailima teaches a similar system for detecting evoked potentials (paragraph 0047 – “Other examples of physiological measurements to provide nData include, but are not limited to, the measurement of body temperature, heart or other cardiac-related functioning using an electrocardiograph (ECG), electrical activity using an electroencephalogram (EEG), event-related potentials (ERPs)…”), using sensory stimulation in the form of computerized stimuli or interaction, or CSI (paragraph 0055 – “As used herein, the term “computerized stimuli or interaction” or “CSI” refers to a computerized element that is presented to a user to facilitate the user's interaction with a stimulus or other interaction. As non-limiting examples, the computing device can be configured to present auditory stimulus or initiate other auditory-based interaction with the user, and/or to present vibrational stimuli or initiate other vibrational-based interaction with the user, and/or to present tactile stimuli or initiate other tactile-based interaction with the user, and/or to present visual stimuli or initiate other visual-based interaction with the use”).
Alailima further teaches that the CSI can be of varying frequency (paragraph 0159 – “The graphical element/output/stimuli 1106a comprises at least one user interface element, user prompt, notification, message, visual element of varying shape, color, color scheme, sizes, rate, frequency of rendering of a graphical output, visual stimuli, computerized stimuli, or the like”),
and teaches the known technique of selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals (paragraph 0161 – “In various embodiments, using effort metric data 1202, one or more training data set are derived to identify, quantify, or qualify one or more user characteristics including but not limited to effort or level of engagement, attention to tasks or user prompts, level of interaction/response time, level of skills, reaction time…effort metric data 1202 enables the modification or adjustment, rate, frequency, or the like, of one or more graphical element/output/stimuli 1106a of FIG. 6 and associated computerized stimuli or interaction”).
Both Sullivan and Alailima both teach within the field of sensory stimulation systems/methods as stated above. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensory stimuli frequency adjustment as taught by Sullivan, to incorporate the sensory stimulation frequency adjustment via reaction time as taught by Alailima, since such modification would predictably result in, for example, assess treatment validation, and/or assess changes in user performance/condition (Alailima paragraphs 0169-0170).
Re. claim 8, the combined invention of Sullivan and Alailima (hereinafter the combined invention) further teaches the method implemented during a use, by the user, of the device of this user (Sullivan paragraph 0026 – “In some embodiments, a system is provided that efficiently and effectively identifies EEG signals associated with SEPs to control a device. In some embodiments, a system is provided that uses flashing lights (e.g., from one or more light-emitting diodes (LEDs) and/or from a computer screen or television (TV) screen) that correspond to commands to/from a user”).
Re. claim 9, the combined invention further teaches the method implemented at different moments during a day (Sullivan paragraph 0026 – “In some embodiments, the flashing lights in the system flash at variable frequencies in a fixed pattern or in non-periodic frequencies”),
and comprising storing at least one frequency attributable to a respective sensory stimulation signal of the sensory stimulation signals, corresponding to a respective moment during that day (Sullivan paragraph 0035 – “…and a data storage 124 (e.g., for storing received EEG signal samples and associated timing data, such as for the flashing LED lights)…”; controller 620, which includes processor as per paragraph 0041, also controls the frequency of the flashing lights as per paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”).
Re. claim 10, the combined invention further teaches the method implemented at different moments during a day, for the user (Sullivan paragraph 0026 – “In some embodiments, the flashing lights in the system flash at variable frequencies in a fixed pattern or in non-periodic frequencies”),
and comprising storing at least one frequency attributable to a respective sensory stimulation signal of the sensory stimulation signals intended for that user, corresponding to a respective moment during that day (Sullivan paragraph 0035 – “…and a data storage 124 (e.g., for storing received EEG signal samples and associated timing data, such as for the flashing LED lights)…”; controller 620, which includes processor as per paragraph 0041, also controls the frequency of the flashing lights as per paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”).
Re. claim 11, Sullivan teaches a non-transitory computer readable medium comprising instructions stored thereon for implementing a method for detecting evoked potentials in a physiological signal of the user (paragraph 0021 – “The invention can be implemented in numerous ways, including as a process; an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored on and/or provided by a memory coupled to the processor”), when said instructions are executed by a processor of a processing circuit, wherein the method comprises:
generating, by a signal generator of the processing circuit, sensory stimulation signals to be applied by a human machine interface intended for the user (paragraph 0026 – “In some embodiments, a system is provided that uses flashing lights (e.g., from one or more light-emitting diodes (LEDs) and/or from a computer screen or television (TV) screen) that correspond to commands to/from a user… As used herein, SEPs generally refer to involuntary EEG signals generated when the user is exposed to (e.g., rapidly) repeating sensory stimuli (e.g., visual, such as a flashing light or another involuntary response to a visual stimulus event, audio, tactile, or other stimulus event)”),
the sensory stimulation signals being periodic (paragraph 0026 – “In some embodiments, the flashing lights in the system flash at variable frequencies in a fixed pattern or in non-periodic frequencies”),
and adjustable in frequency (paragraph 0030 – “In some embodiments, various parameters are adjusted to maximize the EEG signal and increase the visually-evoked potential detection rate, such as light brightness, color, spacing, frequency…”; paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”);
and detecting the evoked potentials in the physiological signals of the user received by an input interface of the processing circuit, in reaction to the generating of the sensory stimulation signals (paragraph 0030 – “In some embodiments, various parameters are adjusted to maximize the EEG signal and increase the visually-evoked potential detection rate, such as light brightness, color, spacing, frequency, duty cycle, and the amount of visual field that is used by the lights. When a visually-evoked potential is detected, then the corresponding command is sent to the controlled device”; paragraph 0030 – “In some embodiments, the EEG detection system 130 detects EEG signals of a user, and the EEG control system 110 includes a processor configured to perform an SEP [Sensory Evoked Potentials] determination algorithm (e.g., a real-time classification algorithm/classifier) for EEG signals detected by EEG detection system 130”).
Sullivan does not expressly teach selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals.
Alailima teaches a similar system for detecting evoked potentials (paragraph 0047 – “Other examples of physiological measurements to provide nData include, but are not limited to, the measurement of body temperature, heart or other cardiac-related functioning using an electrocardiograph (ECG), electrical activity using an electroencephalogram (EEG), event-related potentials (ERPs)…”), using sensory stimulation in the form of computerized stimuli or interaction, or CSI (paragraph 0055 – “As used herein, the term “computerized stimuli or interaction” or “CSI” refers to a computerized element that is presented to a user to facilitate the user's interaction with a stimulus or other interaction. As non-limiting examples, the computing device can be configured to present auditory stimulus or initiate other auditory-based interaction with the user, and/or to present vibrational stimuli or initiate other vibrational-based interaction with the user, and/or to present tactile stimuli or initiate other tactile-based interaction with the user, and/or to present visual stimuli or initiate other visual-based interaction with the use”).
Alailima further teaches that the CSI can be of varying frequency (paragraph 0159 – “The graphical element/output/stimuli 1106a comprises at least one user interface element, user prompt, notification, message, visual element of varying shape, color, color scheme, sizes, rate, frequency of rendering of a graphical output, visual stimuli, computerized stimuli, or the like”),
and teaches the known technique of selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals (paragraph 0161 – “In various embodiments, using effort metric data 1202, one or more training data set are derived to identify, quantify, or qualify one or more user characteristics including but not limited to effort or level of engagement, attention to tasks or user prompts, level of interaction/response time, level of skills, reaction time…effort metric data 1202 enables the modification or adjustment, rate, frequency, or the like, of one or more graphical element/output/stimuli 1106a of FIG. 6 and associated computerized stimuli or interaction”).
Both Sullivan and Alailima both teach within the field of sensory stimulation systems/methods as stated above. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensory stimuli frequency adjustment as taught by Sullivan, to incorporate the sensory stimulation frequency adjustment via reaction time as taught by Alailima, since such modification would predictably result in, for example, assess treatment validation, and/or assess changes in user performance/condition (Alailima paragraphs 0169-0170).
Re. claim 12, Sullivan teaches a device for detecting an evoked potential in a physiological signal from a user (abstract – “An EEG control of devices using Sensory Evoked Potentials (SEPs) (e.g., visually-evoked potentials), is disclosed”) comprising:
a generator of sensory stimulation signals (paragraph 0026 – “In some embodiments, a system is provided that uses flashing lights (e.g., from one or more light-emitting diodes (LEDs) and/or from a computer screen or television (TV) screen) that correspond to commands to/from a user… As used herein, SEPs generally refer to involuntary EEG signals generated when the user is exposed to (e.g., rapidly) repeating sensory stimuli (e.g., visual, such as a flashing light or another involuntary response to a visual stimulus event, audio, tactile, or other stimulus event)”), the generator of sensory stimulation signals being connectable to a human-machine interface adapted for reproducing the sensory stimulation signals generated for the user (figures 7-8),
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the sensory stimulation signals being periodic (paragraph 0026 – “In some embodiments, the flashing lights in the system flash at variable frequencies in a fixed pattern or in non-periodic frequencies”),
and adjustable in frequency (paragraph 0030 – “In some embodiments, various parameters are adjusted to maximize the EEG signal and increase the visually-evoked potential detection rate, such as light brightness, color, spacing, frequency…”; paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”);
and a frequency selector for the sensory stimulation signals (paragraph 0044 – “In some embodiments, the flashing pattern is controlled by the controller 620 (e.g., controlling the frequency of the flashing using an FPGA controller, such as a Xilinx FPGA chip that executes Verilog code)”).
Sullivan does not expressly teach selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals.
Alailima teaches a similar system for detecting evoked potentials (paragraph 0047 – “Other examples of physiological measurements to provide nData include, but are not limited to, the measurement of body temperature, heart or other cardiac-related functioning using an electrocardiograph (ECG), electrical activity using an electroencephalogram (EEG), event-related potentials (ERPs)…”), using sensory stimulation in the form of computerized stimuli or interaction, or CSI (paragraph 0055 – “As used herein, the term “computerized stimuli or interaction” or “CSI” refers to a computerized element that is presented to a user to facilitate the user's interaction with a stimulus or other interaction. As non-limiting examples, the computing device can be configured to present auditory stimulus or initiate other auditory-based interaction with the user, and/or to present vibrational stimuli or initiate other vibrational-based interaction with the user, and/or to present tactile stimuli or initiate other tactile-based interaction with the user, and/or to present visual stimuli or initiate other visual-based interaction with the use”).
Alailima further teaches that the CSI can be of varying frequency (paragraph 0159 – “The graphical element/output/stimuli 1106a comprises at least one user interface element, user prompt, notification, message, visual element of varying shape, color, color scheme, sizes, rate, frequency of rendering of a graphical output, visual stimuli, computerized stimuli, or the like”),
and teaches the known technique of selecting frequencies of the sensory stimulation signals according to a reaction speed of the user to the sensory simulation signals (paragraph 0161 – “In various embodiments, using effort metric data 1202, one or more training data set are derived to identify, quantify, or qualify one or more user characteristics including but not limited to effort or level of engagement, attention to tasks or user prompts, level of interaction/response time, level of skills, reaction time…effort metric data 1202 enables the modification or adjustment, rate, frequency, or the like, of one or more graphical element/output/stimuli 1106a of FIG. 6 and associated computerized stimuli or interaction”).
Both Sullivan and Alailima both teach within the field of sensory stimulation systems/methods as stated above. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the sensory stimuli frequency adjustment as taught by Sullivan, to incorporate the sensory stimulation frequency adjustment via reaction time as taught by Alailima, since such modification would predictably result in, for example, assess treatment validation, and/or assess changes in user performance/condition (Alailima paragraphs 0169-0170).
Re. claim 13, the combined invention further teaches wherein the detection device (Sullivan figure 1, detection system 500) comprises at least:
a processing circuit configured for generating the sensory stimulation signals and selecting at least one frequency (Sullivan paragraph 0041 – “The controller 620 also includes an FPGA 622 (or, in some embodiments, any other form of a processor or software executed on a processor, such as an ASIC or programmed processor)”),
an output interface connected to the processing circuit and connectable to the human-machine interface intended for the user (Sullivan figure 2, output control 118 connected to the processor 114), and
an input interface connected to the processing circuit, for receiving said physiological signal from the user (Sullivan figure 2, EEG detection system 130 connected to the processor 114).
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Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan (US 20100234752 A1 – hereinafter Sullivan) in view of Alailima (US 20200114115 A1 – hereinafter Alailima), and in further view of Heyrend (US 6115631 A – hereinafter Heyrend).
Re. claim 7, the combined invention of Sullivan and Alailima (hereinafter the combined invention) teaches the evoked potential detection method as stated above in claim 1, but does not expressly disclose the method implemented during a calibration phase of the device, the device being intended for the given user.
Heyrend teaches a similar evoked response detection system (abstract – “A method and apparatus for determining the probability of ruminating behavior in a person of known age, sex and use of medication, is provided by generating and measuring a visually evoked response to a certain auditory and visually displayed paradigms”), and further teaches the known technique of implementing a detection method during a calibration phase of the device, the device being intended for this given user (Column 7, lines 36-53: “Each patient was administered a series of evoked potential studies and a quantitative electroencephalogram…A channel-by-channel calibration was performed before and after each recording session”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the evoked potential detection system/method of the combined invention, to incorporate the calibration phase as taught by Heyrend, since such modification would predictably result in acquisition of relevant user data.
Allowable Subject Matter
Claims 2-6 and 14 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: the prior art of record does not explicitly teach the detection method comprising steps of, for a particular sensory stimulation signal of the sensory stimulation signals, the frequency is selected when a reaction latency of the user, between a moment the signal is generated and a moment the evoked potential is detected, when such detection occurs, is below a threshold, as stated in claim 2. Dependent claims 5-6 are further objected due to their dependencies to claim 2.
Furthermore, the prior art of record does not explicitly teach the detection method comprising steps of, adjusting the frequency of the signal to a first frequency, then measuring a reaction latency of the user between the moment the signal is generated and the moment the evoked potential is detected, when such detection occurs, and: if the latency is below a threshold, selecting the first frequency, which comprises a storing of information according to which the first frequency is attributable to the sensory stimulation signal, otherwise, repeating the generating and detecting with a second frequency in place of the first frequency, the second frequency being different from the first frequency, as claimed in claim 3. Dependent claim 4 is further objected due to its dependency to claim 3.
The prior art of record does not expressly teach the detection device comprising the processing circuit which further comprises a memory storing at least some identifiers of respective frequencies of the sensory stimulation signals, and information specific to a portion of said frequencies and according to which the frequencies of said portion are commonly attributable to the sensory stimulation signals, as claimed in claim 14.
Claims 2-6 and 14 remain rejected as per the 35 USC 101 rejection as stated above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Geva (US 20140163328 A1) teaches a similar detection system (abstract – “A method of estimating the likelihood of brain concussion from neurophysiological data…”) which calculates latency differences outside a predetermined range (paragraph 0110).
Dyell (US 20160058287 A1) teaches a patient monitoring system (abstract - “An apparatus for real time monitoring of a patient is provided…”) which includes latency threshold criteria 22 (paragraph 0029).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Anh-Khoa N. Dinh whose telephone number is (571)272-7041. The examiner can normally be reached Mon-Fri 7:00am-4:00pm EST.
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/ANH-KHOA N DINH/Examiner, Art Unit 3796
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