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
Applicant's arguments, See Applicant’s Remarks, filed 10 February, 2026 with respect to the rejection of claims 1, 8, 12, 14, and 15 under 35 USC 102 and the rejection of claims 2-7, 9-11, 13, and 16-20 under 35 USC 103 have been fully considered but they are not persuasive. Specifically, Applicant argues:
Independent claims 1 and 15 recite "storing each respective time series of pressures in a data structure that is looped such that the time series of pressures for each zone is treated as adjacent to the time series of pressures of two other zones." As an example, the data structure 112 described in FIG. 1A of this application has 24 rows and is looped such that the 24th row is treated as being adjacent to both the 23rd row and the 1st row. The Office Action alleges that [0015] of Seok shows this type of data structure. However, the cited portion of Seok merely discusses an offset, relative to a touch input point, that may be expanded or reduced based on the input. Nowhere does Seok describe a looped data structure. Accordingly, Seok fails to anticipate Applicant's independent claims.
The Examiner has carefully considered the argument, however it is not persuasive. Applicant’s Specification describes the looped data structure as a data structure in which the 24th row is treated as being adjacent to both the 23rd row and the 1st row in the case that the data structure has 24 rows such that when a gesture pattern overlaps the 24th row and 1st row, it is still treated as a contiguous pattern (see Applicant’s Specification Paragraph 0063 Referring back to operation 160, comparing the time series of pressures to determine if they match may require additional operations. In the embodiment depicted in FIGS. 1A and 1B, the time series of pressures of the data structure 122 that is looped is split over adjacent zone numbers 24 and 1. The data structure 122 is looped when comparing to the reference data structure 112 such that time series of pressures for adjacent zone numbers 23, 24, 1, and 2 are considered as a subset containing a contiguous time series of pressures resulting from the gesture input 120. The looping may occur before the comparison to the training data, such as part of a pre-processing operation, or as part of the comparison, such as by incrementally shifting which zone is the initial zone when comparing to the reference data structure 112.). As such, the broadest reasonable interpretation of the looped data structure recited in the claims in light of the specification, would include the data structure taught in Seok which applies an offset to the position of the gesture when analyzing the pattern of the gesture in order to treat the gesture as a contiguous pattern regardless of where the pattern occurs on the steering wheel (see Seok Paragraph 0115 The offset d may be expanded or reduced depending on the point, at which the touch input has been received, and accordingly, the touch areas a2, a3 for manipulation may also be changed (into a2', a3', respectively). Paragraph 0120 Besides, the driver may make touch inputs at any points on the steering wheel 100, so the present disclosure is not limited to the aforementioned embodiments.). Therefore, the prior art rejections are maintained.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 8, 12, 14, and 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Seok (U.S. Patent Application Publication 2019/0210630).
Regarding claim 1, Seok teaches a system comprising: a plurality of sensors disposed on a steering wheel of a vehicle to sense contact of a user's hands with the steering wheel of the vehicle (Paragraph 0053 Referring to FIG. 3, the base 110 may include sensor electrodes 111 to 114.), wherein the plurality of sensors are arranged into a plurality of zones that wrap around the steering wheel such that each zone of the plurality of zones is adjacent to two other zones of the plurality of zones (Paragraph 0081 The plurality of sensor electrodes 111 to 114 may have a certain pattern. The sensor electrodes 111 to 114 may include a plurality of first sensor electrodes 111 and 112 and a plurality of second sensor electrodes 113 and 114.); input/output circuitry configured to: continuously receive data from the plurality of sensors (Paragraph 0100 The controller 140 may determine whether a touch input is received from the driver based on an amount of change in capacitance of each sensor electrodes 111 to 114.); and control circuitry configured to: determine a respective time series of pressures for each respective zone of the plurality of zones based on the received data from a subset of sensors of the plurality of sensors that are in each respective zone (Paragraph 0105 As the controller 140 activates the touch areas a2, a3 for manipulation, the driver may be able to enter various commands into the touch areas a2, a3 for manipulation to operate internal components of the vehicle.); store each respective time series of pressures in a data structure that is looped such that the time series of pressures for each zone is treated as adjacent to the time series of pressures of two other zones (Paragraph 0115 The offset d may be expanded or reduced depending on the point, at which the touch input has been received, and accordingly, the touch areas a2, a3 for manipulation may also be changed (into a2', a3', respectively). Paragraph 0120 Besides, the driver may make touch inputs at any points on the steering wheel 100, so the present disclosure is not limited to the aforementioned embodiments.); based on analyzing the data structure that is looped, identifying an action to control at least one element of the vehicle; and performing the action to control the at least one element of the vehicle (Paragraph 0137 Once the controller 140 activates a touch area for manipulation, the driver may be able to enter various commands to the touch area for manipulation. For example, the driver may select a content displayed on the AVN or the cluster by making a touch input on the touch area for manipulation.).
Regarding claim 15, the claim is commensurate with claim 1 with the exception that claim 15 is directed to a method. Therefore, the same prior art can be applied to claim 15 as was applied to claim 1.
Regarding claim 8, Seok teaches the system of claim 1 as set forth above. Seok further teaches wherein the data structure that is looped comprises a table where the last row is considered adjacent to the first row and each row contains the time series of pressures for a zone of the plurality of zones (Paragraph 0115 The offset d may be expanded or reduced depending on the point, at which the touch input has been received, and accordingly, the touch areas a2, a3 for manipulation may also be changed (into a2', a3', respectively). Paragraph 0120 Besides, the driver may make touch inputs at any points on the steering wheel 100, so the present disclosure is not limited to the aforementioned embodiments.).
Regarding claim 12, Seok teaches the system of claim 1 as set forth above. Seok further teaches wherein the time series of pressures for the plurality of zones comprises pressures in two noncontiguous subsets of zones that are higher than the remaining zones of the plurality of zones (Paragraph 0105 As the controller 140 activates the touch areas a2, a3 for manipulation, the driver may be able to enter various commands into the touch areas a2, a3 for manipulation to operate internal components of the vehicle.).
Regarding claim 14, Seok teaches a system comprising: a plurality of sensors disposed on a steering wheel of a vehicle to sense contact of a user's fingers with the steering wheel (Paragraph 0053 Referring to FIG. 3, the base 110 may include sensor electrodes 111 to 114.); input/output circuitry configured to: continuously receive data from the plurality of sensors (Paragraph 0100 The controller 140 may determine whether a touch input is received from the driver based on an amount of change in capacitance of each sensor electrodes 111 to 114.); and control circuitry configured to: identify each of the fingers on the steering wheel based on the received data from the plurality of sensors (Paragraph 0100 The controller 140 may then determine whether the touch input from the driver is a palm touch input or a finger touch input based on a touch area of each sensor electrode 111 to 114, in which the touch input has been entered by the driver.); determine a gesture input from at least one of the fingers to the steering wheel based on the received data from the plurality of sensors (Paragraph 0105 As the controller 140 activates the touch areas a2, a3 for manipulation, the driver may be able to enter various commands into the touch areas a2, a3 for manipulation to operate internal components of the vehicle.); and based on the gesture input, perform an action to control at least one element of the vehicle (Paragraph 0137 Once the controller 140 activates a touch area for manipulation, the driver may be able to enter various commands to the touch area for manipulation. For example, the driver may select a content displayed on the AVN or the cluster by making a touch input on the touch area for manipulation.).
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 2, 3, 5, 10, 16, 17, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of Siversten (U.S. Patent Application Publication 2013/0024071).
Regarding claims 2 and 16, Seok teaches the system/method of claims 1 and 15 as set forth above. However, Seok does not teach the control circuitry further configured to: analyze the data structure that is looped by comparing the time series of pressures of the data structure that is looped to a time series of pressures of a reference data structure that is associated with the action to control at least one element of the vehicle.
Siversten, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system analyzes the input from the user by comparing the input to a reference input in a lookup table to determine an action that the input should control (Paragraph 0051 In some embodiments, the user may program the steering wheel input device 100 to designate gestures and associate commands with the designated gestures. In such embodiments, the user may be setting up or altering the look-up table stored in the memory 118 of the processing system 110. In embodiments allowing for such user programming of the steering wheel input device 100, the processing system 110 comprises a programming unit 119 which facilitates programming of the steering wheel input device 100.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of Siversten which teaches analyzing the input from the user by comparing the input to a reference input in a lookup table to determine an action that the input should control in order to allow the user to personalize the system such that the reference inputs are associated with different actions (See Siversten Paragraph 0051 For example, assuming that the pointer detection surface 132 is capable of displaying visual output, the programming unit 119 may control the pointer detection device 130 so that information (icons, menus, text instructions, etc.) is displayed on the pointer detection surface 132 to allow the user to designate gestures and associate commands with the designated gestures.).
Regarding claims 3 and 17, Seok in view of Siversten teaches the system/method of claims 2 and 16 as set forth above. However, Seok does not teach wherein: the reference data structure comprises a table where each row contains a time series of pressures for a zone of a plurality of training zones; and comparing the time series of pressures of the data structure that is looped to the time series of pressures of the reference data structure comprises: determining a pattern in the time series of pressures of the table of the data structure that is looped matches a pattern in the time series of pressures of the table of the reference data structure, wherein the pattern in the time series of pressures of the data structure that is looped corresponds to different row numbers than the pattern in the time series of pressures of the reference data structure.
Siversten, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system analyzes the input from the user by comparing the input to a reference input in a lookup table to determine an action that the input should control (Paragraph 0051 In some embodiments, the user may program the steering wheel input device 100 to designate gestures and associate commands with the designated gestures. In such embodiments, the user may be setting up or altering the look-up table stored in the memory 118 of the processing system 110. In embodiments allowing for such user programming of the steering wheel input device 100, the processing system 110 comprises a programming unit 119 which facilitates programming of the steering wheel input device 100.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of Siversten which teaches analyzing the input from the user by comparing the input to a reference input in a lookup table to determine an action that the input should control in order to allow the user to personalize the system such that the reference inputs are associated with different actions (See Siversten Paragraph 0051 For example, assuming that the pointer detection surface 132 is capable of displaying visual output, the programming unit 119 may control the pointer detection device 130 so that information (icons, menus, text instructions, etc.) is displayed on the pointer detection surface 132 to allow the user to designate gestures and associate commands with the designated gestures.).
Regarding claims 5 and 19, Seok in view of Siversten teaches the system/method of claims 2 and 16 as set forth above. However, Seok does not teach the input/output circuitry further configured to: receive a request to train the system to perform the action to control the at least one element of the vehicle; and the control circuitry further configured to: generate the reference data structure by: storing, in the reference data structure, a respective time series of pressures for each respective zone of the plurality of zones; and associating the respective time series of pressures for each respective zone stored in the reference data structure with the action to control the at least one element of the vehicle.
Siversten, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system receives an input from the user which is to be used as a reference input in a lookup table for future use as a user command (Paragraph 0051 In some embodiments, the user may program the steering wheel input device 100 to designate gestures and associate commands with the designated gestures. In such embodiments, the user may be setting up or altering the look-up table stored in the memory 118 of the processing system 110. In embodiments allowing for such user programming of the steering wheel input device 100, the processing system 110 comprises a programming unit 119 which facilitates programming of the steering wheel input device 100.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of Siversten which teaches receiving an input from the user which is to be used as a reference input in a lookup table for future use as a user command in order to allow the user to personalize the system such that the reference inputs are associated with different actions (See Siversten Paragraph 0051 For example, assuming that the pointer detection surface 132 is capable of displaying visual output, the programming unit 119 may control the pointer detection device 130 so that information (icons, menus, text instructions, etc.) is displayed on the pointer detection surface 132 to allow the user to designate gestures and associate commands with the designated gestures.).
Regarding claim 10, Seok teaches the system/method of claim 1 as set forth above. However, Seok does not teach the control circuitry further configured to: determine a rate of change of a turn angle of the steering wheel is less than a turn rate threshold, wherein performing the action is in response to determining the rate of change of the turn angle is less than the turn rate threshold.
Seok, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system includes a steering wheel angle sensor which determines a change in angle of rotation of the steering wheel and takes into account the change in angle or rotation of the steering wheel when accepting gesture commands from the user (Paragraph 0048 Moreover, the gesture recognition unit 116 of the processing system 110 is able to perform compensation even while changes in angle of rotation of the steering wheel 200 are taking place. For example, if the above-described directly upward drag gesture is input by the user during an operation of making a left tum, the touch trace formed on the pointer detection surface 132 will be as shown in FIG.10. In this case, the gesture recognition unit 116 is able to recognize the rightward arcing drag gesture as a directly upward drag gesture by combining the pointer detection signal from the pointer detection device 130 and the rotation detection signal from the rotation angle sensor 120.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of Siversten which teaches including a steering wheel angle sensor which determines a change in angle of rotation of the steering wheel and taking into account the change in angle or rotation of the steering wheel when accepting gesture commands from the user in order to compensate for changes in steering wheel angle when receiving gesture inputs from the user (See Siversten Paragraph 0005 In accordance with the embodiments presented herein, the above and other considerations are addressed by a steering wheel input device and a method for the same, in which the steering wheel input device has gesture recognition capabilities and compensates for changes in steering wheel angle to enable recognition of gestures input by a user, even when the steering wheel angle is varied.).
Claim(s) 4, 6, 18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of Siversten and Austin (U.S. Patent Application Publication 2024/0351595).
Regarding claims 4 and 18, Seok in view of Siversten teaches the system/method of claims 2 and 16 as set forth above. However, Seok in view of Siversten does not teach wherein the control circuitry is configured to analyze the data structure that is looped by inputting the time series of pressures of the data structure that is looped into a trained machine learning model, wherein the machine learning model was trained by: accessing a time series of pressures of a training data structure and a corresponding action to control at least one element of the vehicle, wherein the reference data structure is the training data structure; inputting the time series of pressures of the training data structure to output a determined action to control at least one element of the vehicle; and adjusting the machine learning model based on comparing the determined action to control the at least one element of the vehicle with the corresponding action to control the at least one element of the vehicle.
Austin, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system analyzes the input of the user using a machine learning model, wherein the model is trained by accessing a training data set of user inputs which are associated with an output vehicle function (Paragraph 0085 As illustrated, operations 400 begin, at operation 402, with obtaining a plurality of training data instances. In certain embodiments, the training data instances are obtained by model training engine 150 from training data 195 stored in data storage device 130. Each training data instance may include a training input and a training output.), determining an output of the model by inputting the training data to the model (Paragraph 0085 The training input may be associated with at least one label that is the training output. The label may indicate (1) that the user intended to control vehicle settings and/or functions, or alternatively, (2) that the user did not intend to control vehicle settings and/or functions.), and adjusting parameters of the model based on a comparison between the determined output and the training data’s associated output (Paragraph 0091 At operation 418, model training engine 150 determines whether to modify one or more parameters of the machine learning model based on the similarity determined at operation 416.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok in view of Siversten with the teachings of Austin which teaches analyzing the input of the user using a machine learning model, wherein the model is trained by accessing a training data set of user inputs which are associated with an output vehicle function determining an output of the model by inputting the training data to the model and adjusting parameters of the model based on a comparison between the determined output and the training data’s associated output in order to use the machine learning model to recognize the intention of the inputs from the user (See Austin Paragraph 0084 As described above, the machine learning model, subsequent to being trained, may be deployed for generating a prediction indicative of a probability that the user intends to employ a particular user command while operating vehicle 180.).
Regarding claims 6 and 20, Seok in view of Siversten teaches the system/method of claims 2 and 16 as set forth above. However, Seok in view of Siversten does not teach wherein: the reference data structure is generated using a different steering wheel of a different vehicle; and a number of zones in a plurality of training zones that wrap around the different steering wheel of the different vehicle is different than the number of zones in the plurality of zones that wrap around the steering wheel of the vehicle.
Austin, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system uses historical data from a variety of users in order to train the system to recognize inputs from the user (Paragraph 0027 Training data 195 may include historical data for a plurality of users, historical data for a plurality of users of vehicle 180, and/or historical data for a single user of vehicle 180. Training data 195 may be continuously and/or periodically collected over time and stored in data storage device 130.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok in view of Siversten with the teachings of Austin which teaches using historical data from a variety of users in order to train the system to recognize inputs from the user in order to provide a robust training data set to train the system on a variety of different conditions (See Austin Paragraph 0027 Training data 195 may be used as inputs to an input layer of machine learning model(s) 155, stored in memory 185, and may be labeled so as to test the performance of model(s) 155. In machine learning, data labeling is the process of adding one or more meaningful and informative labels to data to provide context to the data such that a machine learning model can learn from these labels.).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of Siversten and Taylor (U.S. Patent Application Publication 2010/0302199).
Regarding claim 7, Seok in view of Siversten teaches the system of claim 2 as set forth above. However, Seok in view of Siversten does not teach a plurality of liquid tactile buttons on the steering wheel; and the control circuitry further configured to: based on the comparing, inflate a liquid tactile button located in a zone of the plurality of zones that corresponds to the time series of pressures of the data structure that is looped, wherein performance of the action to control the at least one element of the vehicle is in response to a user interaction with the liquid tactile button.
Taylor, in the same field of endeavor, teaches a ferromagnetic user interface. The system uses a ferrofluid to create raised surfaces on the user interface (Paragraph 0072 When one of the electrically switchable magnets 802 is energized, a magnetic field is produced. The magnetic field flows through the ferro fluid layer 805, and this causes the ferrofluid to react, as illustrated in FIG. 12. A raised surface region 1200 is created on the surface of the ferrofluid above the electrically switchable magnet 802 that has been activated. A user touching the surface of the user-touchable portion 801 is able to detect the presence of the raised surface region on the ferrofluid layer 805. The flexible membrane 806 is sufficiently compliant for the user to feel the raised surface region through the flexible membrane 806.) which may be implemented on a steering wheel (Paragraph 0080 Other non-planar applications for the haptic user interface device include for example steering wheels for vehicles…).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok in view of Siversten with the teachings of Taylor which teaches using a ferrofluid to create raised surfaces on the user interface of a steering wheel in order to provide haptic feedback to the user (See Taylor Paragraph 0074 For example, the processor 1101 can control the activation of the electrically switchable magnets 802 to cause the surface of the ferrofluid layer 805 to comprise an array of bumps by driving each of the electrically switchable magnets 802 with the same polarity. Alternatively, larger raised areas can be created by driving alternate electrically switchable magnets 802 with different polarities, which causes the magnetic fields from the electrically switchable magnets 802 to combine across multiple magnets. Because the physical surface topology of the user interface device 800 can be computer controlled meaningful haptic feedback can be provided to the user.).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of McMillen (U.S. Patent Application Publication 2016/0375910).
Regarding claim 9, Seok teaches the system of claim 1 as set forth above. However, Seok does not teach wherein the data structure that is looped comprises a circular stack, ring buffer, or circular buffer.
McMillen, in the same field of endeavor, teaches a steering wheel system which uses the driver’s touch input to control functions of the vehicle. The system stores the data representing the user input in a circular buffer (Paragraph 0076 The delta value is not an instantaneous delta, but rather a sum of the differences between the past several samples. The number of samples used is programmable and may be adjusted to suit a particular application and execution cycle. According to a particular class of implementations in which the execution cycle was about 55 cycles per second, about eight samples was found to be an effective number. A circular buffer of n deltas between adjacent samples is maintained and, after each new sample, the delta buffer is summed.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of McMillen which teaches storing the data representing the user input in a circular buffer in order to quickly recognizes changes in force input to the steering wheel (See McMillen Paragraph 0076 To recognize quick changes in force as when a finger moves quickly across a sensors, i.e., a “swipe event,” the change or delta in force (i.e., “del”) is monitored. The delta value is not an instantaneous delta, but rather a sum of the differences between the past several samples.).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of Gu (Chinese Patent Publication CN219406578).
Regarding claim 11, Seok teaches the system of claim 1 as set forth above. However, Seok does not teach the control circuitry further configured to: determine a grip strength of at least one of the user's hands based on the time series of pressures of the data structure that is looped; store the grip strength in a profile of the user; and determine, based on the stored grip strength, that the user has a health condition.
Gu, in the same field of endeavor, teaches an interactive steering wheel device. The system monitors parameters of the driver, including grip strength, and uses the data to diagnose a health condition of the driver (Page 3 line 39 The operation process of the utility model is as follows: the driver holds the steering wheel, the pressure sensor detects the pressure change, the circuit power supply in the main board is turned on, the single chip establishes communication with the mobile phone APP through the Bluetooth, the driver can place the finger at the main board PPG optical module for PPG measurement at the idle time, when the driver stably drives, the main board measures the electrocardio signal, skin electrical activity and grip strength of the driver in real time through the left and right hand electrodes, the data is transmitted to the APP through the Bluetooth, the gravity acceleration sensor transmits the data to the single chip in real time, and the data is also transmitted to the APP through the Bluetooth, APP analyzes the state of the driver through algorithm, and evaluates the fatigue degree and health condition of the driver.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of McMillen which teaches monitoring parameters of the driver, including grip strength, and using the data to diagnose a health condition of the driver in order to alert the driver to a possible health condition (Page 3 line 39 The operation process of the utility model is as follows: the driver holds the steering wheel, the pressure sensor detects the pressure change, the circuit power supply in the main board is turned on, the single chip establishes communication with the mobile phone APP through the Bluetooth, the driver can place the finger at the main board PPG optical module for PPG measurement at the idle time, when the driver stably drives, the main board measures the electrocardio signal, skin electrical activity and grip strength of the driver in real time through the left and right hand electrodes, the data is transmitted to the APP through the Bluetooth, the gravity acceleration sensor transmits the data to the single chip in real time, and the data is also transmitted to the APP through the Bluetooth, APP analyzes the state of the driver through algorithm, and evaluates the fatigue degree and health condition of the driver.).
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Seok in view of Frojdh (WIPO Patent Publication WO2014/085277).
Regarding claim 13, Seok teaches the system of claim 1 as set forth above. However, Seok does not teach wherein the steering wheel comprises handlebars having grips and the plurality of sensors are arranged into a plurality of zones that wrap around the grips such that each zone of the plurality of zones is adjacent to two other zones of the plurality of zones.
Frojdh, in the same field of endeavor, teaches a system for receiving touch inputs from a user of a vehicle in order to control functions of the vehicle. The system may be implemented on a handlebar grip using sensors arranged around the cylindrical handlebar grip (Paragraph 00103 In some embodiments of the present invention, multiple sensors are arranged around the tubular or cylindrical surface of the wheel grip in order to detect when the driver rotates his hand around the grip in the manner of a motorcycle driver revving a motorcycle engine by rotating the handle bar grip. The user interface is configured to control a particular feature by this gesture.).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to have modified Seok with the teachings of Frojdh which teaches implementing the system on a handlebar grip using sensors arranged around the cylindrical handlebar grip in order to provide an alternative to the traditional rotating grip interface for controlling a motorcycle engine (See Frojdh Paragraph 00103 In applications of the present invention to motorcycle handlebars, these sensors provide an alternative to rotating handlebar grips for controlling the speed of the motorcycle engine.).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PATRICK DANIEL MOHL/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666