DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of pre-AIA 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a) the invention was known or used by others in this country, or patented or described in a printed publication in this or a foreign country, before the invention thereof by the applicant for a patent.
Claims 28-32 are rejected under pre-AIA 35 U.S.C. 102(a) as being anticipated by USPN 2014/0074479 to Kassam et al.
Regarding priority date of the present application, the earliest mention of brain activity in the continuity parent cases appears in the parent application with serial number 14/621,922, filed on February 13th 2015. Accordingly the Kassam reference qualifies as prior art with a filing date September 9th 2013 and a provisional date of September 7th 2012.
With regard to claim 28, Kassam discloses a method for biometric identification comprising the steps of:
(a) detecting electronic activity of an individual's brain (paragraphs [0020]-[0021], Kassam discloses determining EEG data or electroencephalogram, which comprises brain electronic activity);
(b) generating a signal derived from the detected electronic activity of the individual's brain (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, both are considered to be signals in the form of an electronic value to be shared as they are transmitted from the biometric detection engine to the music generation engine via a network as shown in Fig. 1 and described in paragraph [0020]); and
(c) outputting an acoustic signal generated as a function of the signal derived from the detected electronic activity (paragraph [0022], The biometric parameters are used by the music generation engine to create one or more music signals which are acoustic signals).
With regard to claim 29, Kassam discloses the method according to claim 28, wherein the acoustic signal comprises an audio signal (paragraph [0033], audio music).
With regard to claim 30, Kassam discloses the method according to claim 29, wherein the audio signal comprises a musical value comprising a plurality of musical elements (paragraphs [0058]-[0059], beats per minute, rhythmic content, melodic module, etc.).
With regard to claim 31, Kassam discloses the method according to claim 30, wherein the plurality of musical elements comprise one or more of key signatures (paragraph [0063], key features), octave scales (paragraph [0063], scale features), major root scales, minor root scales (paragraph [0070], scale degrees, such as major(Ionian), minor (Aeolian)), notes (paragraph [0070], note features), chords, scales (paragraph [0070]), inversions, chromatic scales, meter, tempo (paragraphs [0063]-[0064], [0070]), rhythm (paragraph [0059], [0063], [0066]), beat (paragraph [0058]), cadence, reverb, volume amplitude (paragraph [0065]), velocity, and base intensity (paragraph [0068]).
With regard to claim 32, Kassam discloses the method according to claim 29, wherein the audio signal comprises two or more musical values (See claim 31 for musical values).
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 15, 17-22, 24-27, 33-34, 36-40 and 43 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over the combination of USPNs 2014/0074479 to Kassam et al. and 4,883,067 to Knispel et al.
With regard to claim 15, Kassam discloses a device comprising:
(a) a sensor [comprising at least one electrode] configured to detect electronic activity of an individual's brain (paragraphs [0020]-[0021], Kassam discloses determining EEG data or electroencephalogram, which comprises brain electronic activity. Kassam discloses an image sensor(Fig. 1, 101), for acquiring EEG data, but does not explicitly disclose an electrode for detecting the EEG. Knispel discloses electrodes which are the standard for acquiring brain electronic activity (column 3, lines 43-67). Combination of Kassam and Knispel is addressed below);
(b) a processor (Fig. 1, Biometric Detection Engine 102) configured to analyze the detected electronic activity of the individual's brain and generate a signal derived from the detected electronic activity (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, both are considered to be signals in the form of an electronic value to be shared as they are transmitted from the biometric detection engine to the music generation engine via a network as shown in Fig. 1 and described in paragraph [0020]); and
(c) a transmitter (Fig. 1, Music Generation Engine 103 transmits the generated music to Media Player 104) configured to output an acoustic signal generated as a function of the signal derived from the detected electronic activity (paragraphs [0020]-[0022], and Fig. 1 The biometric parameters are used by the music generation engine to create one or more music signals which are acoustic signals. The biometric detection engine, music generation engine and media player can each be contained within separate computing devices connected via a network. The music generation engine then transmits the music to the media player).
Kassam discloses an image sensor(Fig. 1, 101), for acquiring EEG data, but does not explicitly disclose an electrode for detecting the EEG. Knispel discloses electrodes which are the standard for acquiring brain electronic activity. Knispel uses the electrodes to convert the EEG into electrical signals which are converted into music by synthesizers (See abstract and column 3, lines 43-67). Therefore it would have been obvious to one of ordinary skill in the art before time of filing to use the electrodes to gather EEG data in combination with the EEG data collection of Kassam in order to turn the collected EEG data into musical signals.
With regard to claim 17, Kassam discloses wherein the acoustic signal comprises an audio signal (paragraph [0033], audio music).
With regard to claim 18, Kassam discloses wherein the audio signal comprises a musical value comprising a plurality of musical elements (paragraphs [0058]-[0059], beats per minute, rhythmic content, melodic module, etc.).
With regard to claim 19, Kassam discloses wherein the plurality of musical elements comprise one or more of key signatures (paragraph [0063], key features), octave scales (paragraph [0063], scale features), major root scales, minor root scales (paragraph [0070], scale degrees, such as major(Ionian), minor (Aeolian)), notes (paragraph [0070], note features), chords, scales (paragraph [0070]), inversions, chromatic scales, meter, tempo (paragraphs [0063]-[0064], [0070]), rhythm (paragraph [0059], [0063], [0066]), beat (paragraph [0058]), cadence, reverb, volume amplitude (paragraph [0065]), velocity, and base intensity (paragraph [0068]).
With regard to claim 20, Kassam discloses the device according to claim 17, wherein the audio signal comprises two or more musical values (See claim 19).
With regard to claim 21, Kassam does not disclose wherein the signal derived from the detected electronic activity is indicative of the individual's emotional state. EEGs are known to be used to indicate emotional state. Knispel teaches that EEG analysis methods provide maps of the brain that indicate what EEG activity are associated with particular states of emotion, cognition and consciousness (column 22, lines 12-19). Therefore it would have been obvious to one of ordinary skill in the art before time of filing to use the EEG data as an indicator of emotional state.
With regard to claim 22, Kassam does not disclose, wherein the audio signal is indicative of the individual's emotional state. Knispel discloses that audio signals or music are determined as a means to enhance or regulate emotional state by using the EEG for determining emotional brain mapping data. Specifically Knispel states (column 22, lines 12-19): “In addition, EEG computer analysis methods, such as BEAM developed by Frank Duffy, are providing extensive maps of the brain that indicate what EEG activity in which regions of the brain are associated with particular states of emotion, cognition and consciousness. This information can be used as a guide for designing resonance feedback protocols and in selecting regions of the brain for resonance stimulation.” Therefore it would have been obvious to one of ordinary skill in the art before time of filing to create music for resonance simulation for creating music audio signals based on and indicative of the determined EEG emotional state data.
With regard to claim 24, Kassam discloses wherein the signal derived from the detected electronic activity comprises a digital data signal (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, both are considered to be digital data signals in the form of an electronic value to be shared as they are transmitted from the biometric detection engine to the music generation engine).
With regard to claim 25, Kassam does not disclose wherein the processor is further configured to cause the presentation of the detected electronic activity as an image comprising the visible light spectrum. Knispel discloses presentation of detected EEG data in the form of a visible image displaying detected alpha waves (Figs. 13a-13b and column 20, lines 59-67). Therefore it would have been obvious to one of ordinary skill in the art before time of filing to display an image of the detected EEG data in order to visualize the EEG activity).
With regard to claim 26, Kassam discloses wherein the device further comprises a network interface configured to enable the transmission of communications between the device and a communications network comprising a plurality of communication nodes, and the transmitter is configured to output the acoustic signal in response to a communication received by the device from a communications network node (paragraphs [0020]-[0022], and Fig. 1 The biometric detection engine, music generation engine and media player can each be contained within separate computing devices connected via a network. The media player plays music from the music generation engine in response to a request to play the music signal).
With regard to claim 27, Kassam discloses wherein the device is configured to transmit the digital data signal through the network interface to a communications network node, and the transmitter is configured to output the acoustic signal in response to a communication received by the device from the communications network node (paragraphs [0020]-[0022], and Fig. 1 The biometric detection engine, music generation engine and media player can each be contained within separate computing devices connected via a network. The media player plays music from the music generation engine in response to a request to play the music signal).
With regard to claim 33, Kassam discloses a system comprising:
(1) a communication network comprising at least one communications network node (Fig. 1 and paragraph [0020], Fig. 1 displays elements each contained within separate computing devices, communicatively connected via a network); and
(2) a device comprising a communications interface configured to enable transmission of communications between the device and a communications network node (Fig. 1, each of the elements are considered devices contained within separate computing devices, communicatively connect via a network),
a sensor [comprising at least one electrode] configured to detect electronic activity of an individual's brain, a processor (paragraphs [0020]-[0021], Kassam discloses determining EEG data or electroencephalogram, which comprises brain electronic activity. Kassam discloses an image sensor(Fig. 1, 101), for acquiring EEG data, but does not explicitly disclose an electrode for detecting the EEG. Knispel discloses electrodes which are the standard for acquiring brain electronic activity (column 3, lines 43-67). Combination of Kassam and Knispel is addressed below), and
a transmitter (Fig. 1, biometric detection engine 102 is configured to gather EEG data for creating a biometric for generating an acoustic signal) configured to output an acoustic signal, the device configured to:
(a) detect electronic activity of an individual's brain (paragraphs [0020]-[0021], Kassam discloses determining EEG data or electroencephalogram, which comprises brain electronic activity);
(b) generate a signal derived from the detected electronic activity of the individual's brain (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, both are considered to be signals in the form of an electronic value to be shared as they are transmitted from the biometric detection engine to the music generation engine via a network as shown in Fig. 1 and described in paragraph [0020]);
(c) transmit the signal derived from the detected electronic activity to a communications network node (paragraph [0022], The biometric parameters are sent to the music generation engine 103 from the biometric detection engine 103 both of which may be contained within a separate computing devices communicatively connected via a network);
(d) receive a digital data communication from the communication network node, wherein the digital data communication is generated as a function of the signal derived from the detected electronic activity (paragraphs [0021]-[0022], The music generation engine 103 receives the communication across a network from the biometric detection engine 102); and
(e) output an acoustic signal generated as a function of the signal derived from the detected electronic activity (paragraphs [0021]-[0022], The music generation engine 103 generates a music signal which is output as a signal to a media player 104).
Kassam discloses an image sensor(Fig. 1, 101), for acquiring EEG data, but does not explicitly disclose an electrode for detecting the EEG. Knispel discloses electrodes which are the standard for acquiring brain electronic activity. Knispel uses the electrodes to convert the EEG into electrical signals which are converted into music by synthesizers (See abstract and column 3, lines 43-67). Therefore it would have been obvious to one of ordinary skill in the art before time of filing to use the electrodes to gather EEG data in combination with the EEG data collection of Kassam in order to turn the collected EEG data into musical signals.
With regard to claim 34, Kassam discloses wherein the device is configured to transmit the signal derived from the detected electronic activity as a digital data communication (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, both are considered to be digital data signals in the form of an electronic value to be shared as they are transmitted from the biometric detection engine to the music generation engine).
With regard to claim 36, Kassam discloses wherein the acoustic signal is an audio signal (paragraph [0033], audio music).
With regard to claim 38, Kassam discloses wherein the device is further configured to analyze the individual's detected electronic activity (paragraph [0021], The EEG data is used to determine a biometric signal and biometric parameter, which is interpreted as analyzing the detected electronic activity).
With regard to claim 39, Kassam discloses wherein the communications network node is configured to analyze the signal derived from the detected electronic activity (paragraphs [0021]-[0022], The music generation engine 103 receives the communication/signal across a network from the biometric detection engine 102. The music generation engine 103 is considered a network node that analyzes the biometric signal in order to generate music).
With regard to claim 40, Kassam discloses wherein the communications network node is configured to generate a digital data communication as a function of the signal derived from the detected electronic activity (paragraphs [0021]-[0022], The music generation engine 103 receives the communication/signal across a network from the biometric detection engine 102. The music generation engine 103 is considered a network node that analyzes the biometric signal in order to generate music. The music is then transmitted as a digital data communication to the media player 104).
With regard to claim 43, Kassam discloses wherein the audio signal comprises a plurality of musical elements and the system further comprises an input device configured to enable the individual to select the arrangement of one or more of the musical elements (paragraphs [0070], [0072]-[0073], the user profile is used along with the input biometric information are used to select the musical elements, which “provide the user with a degree of freedom to select how the music signal is generated that is also directly encouraging a user to optimize their participation in the image capture process.”).
Claims 16 and 35 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over the combination of USPNs 2014/0074479 to Kassam et al. and 4,883,067 to Knispel et al. and further in view of 2014/0050321 to Albert et al.
With regard to claims 16 and 35, Kassam and Knispel disclose the device according to claim 15, but do not disclose wherein the acoustic signal comprises an ultrasonic signal.
Albert discloses a system for the transmission of health data such as EEGs with ultrasonic signals (paragraphs [0005]-[0008], [0046], [0048] and [0079]). Therefore it would have been obvious to one of ordinary skill in the art before time of filing to use an ultrasonic signal to transmit health information such as EEG data as taught by Albert in combination with the EEG recording and transmission of Kassam in order to transmit EEG data.
Claims 23 and 37 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over the combination of USPNs 2014/0074479 to Kassam et al. and 4,883,067 to Knispel et al. and further in view of 2007/0225585 to Washbon.
With regard to claims 23 and 37, Kassam and Knispel do not explicitly disclose wherein the sensor comprises a capacitive sensor. Kassam and Knispel both disclose obtaining EEG data and Knispel discloses using electrodes. Washbon discloses an EEG headset that uses capacitive electrodes (paragraph [0007]). Therefore it would have been obvious to one of ordinary skill in the art before the time of filing to use a capacitive electrode sensor as taught by Washbon in combination with the electrode sensors taught by Knispel for obtaining EEG data.
Claims 41-42 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over the combination of USPNs 2014/0074479 to Kassam et al. and 4,883,067 to Knispel et al. and further in view of 2008/0229408 to Dinges et al.
With regard to claims 41-42, Kassam discloses using an EEG as a biometric signal and Kassam and Knispel both disclose analyzing the EEG of a specific user and a unique user profile, but they do not explicitly teach wherein the communications network node is configured to identify (and/or authenticate -from claim 42) the individual based on the signal derived from the detected electronic activity transmitted by the device.
EEGs are known to be used as a biometric signal for identifying an individual. Dinges discloses a system for access control based on brain patterns or EEG data and teaches at paragraph [0006]: “In this way it is possible to identify a user with absolute reliability and to unambiguously authenticate the same. Furthermore, the unmistakable biometric identification is used in security checking or identification, with it being possible to use evoked electrical potential, such as EEG signals (electroencephalogram) for accurate, unavoidable identification and authentication, including authorization.”
Therefore it would have been obvious to one of ordinary skill in the art before time of filing to use the biometric EEG user profile taught by Kassam as a user identification and authentication biometric as taught by Dinges in order to identify and authenticate the user.
With regard to claim 42, the discussion of claim 41 applies.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WESLEY J TUCKER whose telephone number is (571)272-7427. The examiner can normally be reached 9AM-5PM Monday-Friday.
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/WESLEY J TUCKER/Primary Examiner, Art Unit 2661