阅读说明：本技术 触觉装置操作 (Haptic device operation ) 是由 陈一凡 阿布舍克·夏尔马 汪谦益 史蒂文·林 于 2017-06-27 设计创作，主要内容包括：一种系统,包括被编程为识别音频输入的多个音频幅度的计算机。所述计算机被编程为识别相应识别的音频幅度之间的音频输入的多个时间间隔。所述计算机被编程为基于识别的音频幅度和所述时间间隔来映射触觉模式。所述计算机被配置为致动马达以输出所述触觉模式。(A system includes a computer programmed to identify a plurality of audio magnitudes of an audio input. The computer is programmed to identify a plurality of time intervals of the audio input between respective identified audio amplitudes. The computer is programmed to map haptic patterns based on the identified audio amplitude and the time interval. The computer is configured to actuate a motor to output the haptic pattern.)

1. A system comprising a computer programmed to:

identifying a plurality of audio amplitudes of an audio input;

identifying a plurality of time intervals of the audio input between respective identified audio magnitudes;

mapping a haptic pattern based on the identified audio amplitude and the time interval; and

actuating a motor to output the haptic pattern.

2. The system of claim 1, wherein the computer is further programmed to identify a frequency band for the audio input and apply a filter to the audio input based on the frequency band.

3. The system of claim 2, wherein the computer is further programmed to identify the time interval based on the filtered audio input.

4. The system of claim 2, wherein the computer is further programmed to identify a plurality of dominant frequencies of the filtered audio input.

5. The system of claim 4, wherein the computer is further programmed to identify the time interval based on the identified time when the respective audio amplitudes of two of the plurality of dominant frequencies are the same amplitude.

6. The system of claim 2, wherein the computer is further programmed to identify a second frequency band and apply a second filter to the audio input based on the second frequency band.

7. The system of claim 6, wherein the computer is further programmed to map a first haptic pattern based on the filtered audio input and a second haptic pattern based on the second filtered audio input.

8. The system of claim 1, wherein the computer is further programmed to adjust a rotational speed of the motor based on the haptic pattern.

9. The system of claim 1, wherein upon determining that the duration of the audio input exceeds a duration threshold, the computer is further programmed to receive a user input identifying a portion of the audio input having a duration less than the duration threshold, and map a haptic pattern based on the identified portion of the audio input.

10. The system of claim 1, wherein the motor is disposed in a portable device, and the computer is further programmed to instruct the portable device to actuate the motor to output the haptic pattern.

11. A method, comprising:

identifying a plurality of audio amplitudes of an audio input;

identifying a plurality of time intervals of the audio input between respective identified audio magnitudes;

mapping a haptic pattern based on the identified audio amplitude and the time interval; and

actuating a motor to output the haptic pattern.

12. The method of claim 11, further comprising identifying a frequency band for the audio input and applying a filter to the audio input based on the frequency band.

13. The method of claim 12, further comprising identifying the time interval based on the filtered audio input.

14. The method of claim 12, further comprising identifying a plurality of dominant frequencies of the filtered audio input.

15. The method of claim 14, further comprising identifying the time interval based on an identified time when respective audio amplitudes of two of the plurality of major frequencies are the same amplitude.

16. The method of claim 12, further comprising identifying a second frequency band, and applying a second filter to the audio input based on the second frequency band.

17. The method of claim 16, further comprising mapping a first haptic pattern based on the filtered audio input and mapping a second haptic pattern based on the second filtered audio input.

18. The method of claim 11, further comprising adjusting a rotational speed of the motor based on the haptic pattern.

19. The method of claim 11, wherein upon determining that the duration of the audio input exceeds a duration threshold, the method further comprises receiving a user input identifying a portion of the audio input having a duration less than the duration threshold, and mapping a haptic pattern based on the identified portion of the audio input.

20. The method of claim 11, wherein the motor is disposed in a portable device, and the method further comprises instructing the portable device to actuate the motor to output the haptic pattern.

Background

The electronic device may comprise a haptic device. The haptic device may be programmed to generate a vibration pattern that causes the electronic device to vibrate to provide a haptic output. However, a problem is that current systems have limited ability to generate a variety of haptic outputs.

Drawings

Fig. 1 is a block diagram of an exemplary system for actuating a wearable device.

Fig. 2 shows an exemplary audio input in the time domain.

Fig. 3 shows the audio input of fig. 2 in the frequency domain.

Fig. 4 shows a plurality of main frequencies of an audio input.

Fig. 5 shows a plurality of time intervals determined based on the dominant frequency.

FIG. 6 shows a haptic pattern based on time interval and dominant frequency mapping.

Fig. 7 shows an exemplary motor installed in a wearable device.

FIG. 8 is a block diagram of an exemplary process for determining a haptic mode.

Detailed Description

A system comprising a computer programmed to: identifying a plurality of audio amplitudes of an audio input; identifying a plurality of time intervals of the audio input between respective identified audio amplitudes; mapping the haptic pattern based on the identified audio amplitude and time interval; and actuating the motor to output the haptic pattern.

The computer may also be programmed to identify a frequency band for the audio input and apply a filter to the audio input based on the frequency band. The computer may also be programmed to identify the time interval based on the filtered audio input.

The computer may also be programmed to identify a plurality of dominant frequencies of the filtered audio input. The computer may be further programmed to identify the time interval based on the identified time when respective audio amplitudes of two of the plurality of dominant frequencies are the same amplitude.

The computer may also be programmed to identify a second frequency band and apply a second filter to the audio input based on the second frequency band. The computer may also be programmed to map a first haptic pattern based on the filtered audio input and map a second haptic pattern based on the second filtered audio input.

The computer may also be programmed to adjust a rotational speed of the motor based on the haptic pattern.

Upon determining that the duration of the audio input exceeds a duration threshold, the computer may be further programmed to receive a user input identifying a portion of the audio input having a duration less than the duration threshold, and map a haptic pattern based on the identified portion of the audio input.

The motor may be disposed in a portable device, and the computer may be further programmed to instruct the portable device to actuate the motor to output the haptic pattern.

One method comprises the following steps: identifying a plurality of audio amplitudes of an audio input; identifying a plurality of time intervals of the audio input between respective identified audio amplitudes; mapping the haptic pattern based on the identified audio amplitude and time interval; and actuating the motor to output the haptic pattern.

The method may also include identifying a frequency band for the audio input and applying a filter to the audio input based on the frequency band. The method may also include identifying the time interval based on the filtered audio input.

The method may also include identifying a plurality of dominant frequencies of the filtered audio input. The method may further include identifying the time interval based on the identified time when respective audio amplitudes of two of the plurality of dominant frequencies are the same amplitude.

The method may further include identifying a second frequency band; and applying a second filter to the audio input based on the second frequency band. The method may also include mapping a first haptic pattern based on the filtered audio input and mapping a second haptic pattern based on the second filtered audio input.

The method may further include adjusting a rotational speed of the motor based on the haptic pattern.

Upon determining that the duration of the audio input exceeds a duration threshold, the method may further comprise: receiving a user input identifying a portion of the audio input having a duration less than the duration threshold and mapping a haptic pattern based on the identified portion of the audio input.

The motor may be disposed in a portable device, and the method may further include instructing the portable device to actuate the motor to output the haptic pattern.

A computing device programmed to perform any of the above method steps is also disclosed. A vehicle including the computing device is also disclosed. A computer program product is also disclosed, comprising a computer readable medium storing instructions executable by a computer processor to perform any of the above method steps.

Fig. 1 illustrates an example system 100 for mapping haptic patterns of a wearable device 140 based on audio input. The computer 105 in the vehicle 101 is programmed to receive the collected data 115 from the one or more sensors 110. For example, the data 115 for the vehicle 101 may include a location of the vehicle 101, a location of a target, and the like. The location data may be in a known form, e.g., geographic coordinates, such as latitude and longitude coordinates obtained via known navigation systems using the Global Positioning System (GPS). Further examples of data 115 may include measurements of systems and components of vehicle 101, such as the speed of vehicle 101, the trajectory of vehicle 101, and so forth.

As used herein, the term "mapping" when used as an action word in the context of mapping haptic modes means "assigned to action". Computer 105 "maps" the haptic pattern to the action, such that when the action is recognized, computer 105 outputs the haptic pattern. The action may be an event and/or a condition that may require attention of the user, as described below.

As is known, the computer 105 is typically programmed for communication over a network (e.g., including a communication bus) of the vehicle 101. Via a network, bus, and/or other wired or wireless mechanism (e.g., a wired or wireless local area network in vehicle 101), computer 105 may transmit and/or receive messages to and/or from various devices in vehicle 101, such as controllers, actuators, sensors, etc., including sensors 110. Alternatively or additionally, in cases where computer 105 actually includes multiple devices, a vehicle network may be used for communication between the devices, represented in this disclosure as computer 105. In addition, the computer 105 may be programmed to communicate with a network 125, which, as described below, may include various wired and/or wireless networking technologies, such as cellular, broadband, or the like,

Low power consumption

(BLE), wired and/or wireless packet networks, etc.

The data storage 106 may be of any known type, such as a hard disk drive, a solid state drive, a server, or any volatile or non-volatile media. The data storage device 106 may store the collected data 115 sent from the sensors 110.

The sensor 110 may include various devices. For example, as is known, various controllers in the vehicle 101 may operate as sensors 110 to provide data 115, e.g., data 115 related to vehicle speed, acceleration, position, subsystem and/or component status, etc., via a vehicle 101 network or bus. Additionally, other sensors 110 may include cameras, motion detectors, and the like, i.e., sensors 110 are used to provide data 115 to evaluate the location of an object, determine the presence of a user, and the like. The sensors 110 may also include a short range radar, a long range radar, and/or an ultrasonic transducer.

The collected data 115 may include various data collected in the vehicle 101. Examples of collected data 115 are provided above, and further, data 115 is typically collected using one or more sensors 110, and may additionally include data calculated from the collected data in computer 105 and/or at server 130. In general, the collected data 115 may include any data that may be collected by the sensors 110 and/or calculated from such data.

Vehicle 101 may include a plurality of vehicle components 120. As used herein, each vehicle component 120 includes one or more hardware components adapted to perform a mechanical function or operation (such as moving the vehicle, slowing or stopping the vehicle, steering the vehicle, etc.). Non-limiting examples of components 120 include propulsion components (including, for example, an internal combustion engine and/or an electric motor, etc.), transmission components, steering components (e.g., which may include one or more of a steering wheel, a steering rack, etc.), braking components, park assist components, adaptive cruise control components, adaptive steering components, and the like.

When the computing device 105 operates the vehicle 101, the vehicle 101 is an "autonomous" vehicle 101. For purposes of this disclosure, the term "autonomous vehicle" is used to refer to vehicle 101 operating in a fully autonomous mode. A fully autonomous mode is defined as a mode in which each of propulsion (typically via a powertrain including an electric motor and/or an internal combustion engine), braking, and steering of vehicle 101 is controlled by computing device 105. A semi-autonomous mode is a mode in which at least one of propulsion (typically via a powertrain including an electric motor and/or an internal combustion engine), braking, and steering of vehicle 101 is controlled, at least in part, by computing device 105 rather than a human operator.

The system 100 may also include a network 125 connected to the server 130 and the data storage device 135. Computer 105 may also be programmed to communicate via network 125 with one or more remote sites, such as server 130, which may include data storage 135. Network 125 represents the means by which vehicle computer 105 may communicate withOne or more mechanisms for remote server 130 to communicate. Thus, the network 125 may be one or more of a variety of wired or wireless communication mechanisms, including any desired combination of wired (e.g., cable and fiber) and/or wireless (e.g., cellular, wireless, satellite, microwave, and radio frequency) communication mechanisms, as well as any desired network topology (or topologies where multiple communication mechanisms are utilized). Exemplary communication networks include wireless communication networks providing data communication services (e.g., using

Low power consumption

(BLE), IEEE802.11, vehicle-to-vehicle (V2V), such as Dedicated Short Range Communication (DSRC), etc., a Local Area Network (LAN), and/or a Wide Area Network (WAN), including the internet.

The system 100 may include a wearable device 140. As used herein, a "wearable device" is a portable computing device that includes structure to facilitate wearing on a person's body (e.g., as a watch or bracelet, as a pendant, etc.), and includes memory, a processor, a display, and one or more input mechanisms (such as a touchscreen, buttons, etc.), as well as hardware and software for wireless communication such as described herein. The wearable device 140 has a size and shape that fits or is worn on the human body (e.g., a watch-like structure including a bracelet band, etc.), and thus will typically have a display that is smaller (e.g., is 1/3 or 1/4 of area) than the user device 150. For example, the wearable apparatus 140 may be a watch, a smart watch, a vibrating device, or the like, including a device for using IEEE802.11,BLE and/or cellular communication protocols. Further, wearable device 140 may use such communication capabilities to communicate via network 125 and also, for example, use

Directly connected with a vehicleThe vehicle computer 105 communicates. The wearable device 140 includes a wearable device processor 145.

System 100 may include user device 150. As used herein, a "user device" is a portable, non-wearable computing device that includes memory, a processor, a display, and one or more input mechanisms (such as a touchscreen, buttons, etc.), as well as hardware and software for wireless communication such as described herein. User device 150 is "non-wearable" meaning that it is not provided with any structure that is worn on the human body; for example, the smartphone user device 150 does not have a size or shape that fits to a human body, and typically must be carried in a bag or handbag, and is wearable on the human body only if it is equipped with a special housing (e.g., with an attachment that wraps around a belt that passes through the human body), and thus the smartphone user device 150 is not wearable. Thus, the user device 150 may be any of a variety of computing devices, such as a smartphone, a tablet, a personal digital assistant, and the like, that include a processor and memory. The user device 150 may communicate with the vehicle computer 105 and the wearable device 140 using the network 125. For example, the user device 150 and the wearable device 140 may be communicatively coupled to each other and/or to the vehicle computer 105 using wireless technology such as described above. The user device 150 includes a user device processor 155.

As used herein, a "haptic mode" is a set of instructions for activating and deactivating a motor (e.g., an electric eccentric rotary motor) to generate a particular vibration pattern.

Fig. 2 shows a chart 200 of exemplary audio input 205 collected by user device 150 and/or wearable device 140. The audio input 205 may be, for example, a pre-recorded audio file, an input from a microphone in the user device 150, or the like. The computer 105 and/or user device processor 155 may receive user input identifying a portion 210 of the audio input 205. The user may select a prompt on the screen of user device 150 to record an audio input (e.g., a voice input) with a microphone in user device 150 and/or wearable device 140. Alternatively, the user may select the data storage device stored on user device 150: (Not shown) of the audio file. The audio input 205 is shown in fig. 2 as a graph having the well-known amplitude in decibels full scale (dBFS) on the vertical axis and time in seconds(s) on the horizontal axis. A portion 210 of the audio input 205 may be isolated to determine the haptic pattern. May be based on a duration threshold t₀To determine the portion 210 of the audio input 205, the computer 105 and/or user device processor 155 has previously determined the duration threshold as the length of the haptic pattern. The audio input 200 may have different durations and may be based on a particular, previously determined, duration threshold t₀To determine the haptic pattern. Thus, the haptic patterns determined from the plurality of audio inputs 200 may have the same duration. For example, the haptic pattern may have a duration of 500 milliseconds (ms), and the audio input 205 may have a duration of greater than 500ms (e.g., 5000 ms).

The user may provide an input indicating a 500ms portion 210 of the audio input 205 from which the user device processor 155 may map the haptic pattern. For example, as shown in fig. 2, audio input 205 may be displayed on a touch screen display of user device 150, and the box indicated as portion 210 may be moved along a horizontal axis of audio input 205 by tactile input on the touch screen display of user device 150. The user may select portion 210 of audio input 205 by moving the box along the touch screen display to a preferred portion of audio input 205. In addition, user device processor 155 may determine a plurality of haptic patterns, each haptic pattern having a duration t₀Which is determined continuously for the entire duration or a smaller portion of the audio input 205. For example, the user device processor 155 may determine that a haptic pattern is mapped for 3000ms in the 5000ms duration audio input 205. The user device processor 155 can map the haptic patterns for each 500ms portion 210 of the audio input 205 until the duration of all haptic patterns is 3000ms, i.e., 6 haptic patterns. The user device processor 155 may then store the 6 haptic patterns of 500ms duration as a single haptic pattern of 3000ms duration. Instead ofInstead, the computer 105 and/or user device processor 155 may select a portion 210 of the audio input 205, e.g., the first 500ms of the audio input 205.

Fig. 3 shows a graph 300 of the frequency of an exemplary portion 210 of the audio input 205. The graph 300 of fig. 3 has the amplitude of the audio input in dBFS on the vertical axis and the frequency of the audio input in kilohertz (kHz) on the horizontal axis. The portion 210 of the audio input 205 identified in fig. 2 may be decomposed into its component frequencies and the magnitude of each component frequency using known techniques, such as Fast Fourier Transform (FFT), laplace transform, Z transform. The user device processor 155 may identify the frequency with the largest magnitude, i.e., the dominant frequency f'. As used herein, the "dominant" frequency is the frequency having the largest amplitude in portion 210. The user device processor 155 may determine the primary band as f' -f^*，f′+f^*]Wherein f is^*Is a predetermined offset defining the width of the main frequency band. Alternatively, the user device processor 155 may identify another frequency f₀And determines the frequency band f₀-f^*，f₀+f^*]. The user device processor 155 may identify a plurality of primary frequency bands based on the identified frequencies f' for the plurality of portions 210 of the audio input 205.

FIG. 4 shows the duration t in the portion 210 of the audio input 205₀Exemplary frequency f in the inner frequency domain₁，f₂Is shown in graph 400. Graph 400 in fig. 4 shows amplitude in dBFS on the vertical axis and time in seconds on the horizontal axis. The user device processor 155 may isolate frequencies by applying a filter (e.g., a band pass filter) to the portion 210 of the audio input 205 based on the primary frequency band. When the filter is a band pass filter, the filter removes frequencies from the portion 210 of the audio input 205 that are outside the main frequency band. Frequency f shown in FIG. 4₁，f₂Are exemplary frequencies representing two of the plurality of frequencies in the main frequency band. The user device processor 155 may identify a different number of frequencies. Alternatively or additionally, computer 105 may apply a plurality of band pass filters based on a plurality of determined dominant frequency bandsThe filter to generate a plurality of filtered audio inputs, e.g. based on a frequency f₂、[f₂-f^*，f₂+f^*]A second filtered audio input of a second frequency band of the basis.

Fig. 5 shows a graph 500 of the absolute value of the amplitude of the audio input 205 and the time interval delta determined by comparing the amplitude of the frequencies in the main frequency band. As shown in FIG. 4, the portion 210 of the audio input 205 may be represented as two frequencies f in the primary frequency band₁，f₂. The user device processor 155 may identify the current frequency f₁Is equal to the secondary frequency f₂A plurality of time values t of the amplitude of (d). The user device processor 155 may determine a plurality of time intervals δ that elapse between two consecutive time values t, between the start of the audio input and the first time value t, and between the last time value t and the end of the audio input 205. That is, when the frequency f is₁，f₂Begins to exceed the frequency f₁，f₂The user device processor 155 may define the time value t as the start of a new time interval δ. In the example of fig. 5, the frequency f₁，f₂Defining seven time intervals delta_t1，δ_t2，δ_t3，δ_t4，δ_t5，δ_t6，δ_t7Six time values t₁，t₂，t₃，t₄，t₅，t₆And (c) are crossed. When the user device processor 155 identifies multiple frequencies in the primary frequency band (e.g., f for n frequencies)₁，f₂，f₃，...f_n) When the frequency having the largest amplitude is different from the frequency having the largest amplitude of the previous time value t (i.e., when the frequency having the largest amplitude is changed), the user device processor 155 defines the next time interval δ based on the time value t_t。

Within each time interval δ, computer 105 may identify the interval dominant frequency, i.e., within a particular time interval δ_tThe frequency with the highest amplitude (with the alternate major amplitude a) in the defined section. For example, whileInterval delta between_t1In that the interval main frequency is of interval main amplitude A₁Frequency f of₂. I.e. the dominant frequency of the entire audio input 205 may not be the interval dominant frequency of the particular time interval delta.

FIG. 6 illustrates an example of the identified interval principal amplitude A from the frequency domain shown by computer 105₁-A₇To determine a graph 600 of haptic patterns 605. The haptic pattern 605 is shown as a graph having time in ms on the horizontal axis and motor rotational speed ω in revolutions per minute (rpm) on the vertical axis. For each time interval delta_tThe computer 105 and/or the user device processor 155 are based on the time interval delta_tThe amplitude a of the interval main frequency of (c) assigns the motor speed ω. In the example of FIG. 6, the haptic pattern 605 defines seven motor speeds ω₁，ω₂，ω₃，ω₄，ω₅，ω₆，ω₇. The eccentric motor 700 may be actuated according to the rotational speed ω of the haptic pattern, as described below. The computer 105 and/or the user device processor 155 determines an interval pattern for each time interval δ based on the interval dominant frequency. The interval master frequency may define a pattern of actuation motor 700 starts and stops based on the magnitude and value of the interval master frequency.

The example haptic pattern 605 is shown as a square wave, where the wearable device processor 145 is programmed to actuate the motor 700 at a motor speed ω at the beginning of each non-zero portion of the square wave and deactivate the motor 700 at the end of each non-zero portion of the square wave. The length along the time axis of the non-zero portion of the square wave is defined as the "pulse width". The pulse width of the square wave is based on the ratio of the interval main frequency to the main frequency of the current time interval δ:

wherein f'_δIs interval dominant frequency, f'_δ，maxIs the maximum interval dominant frequency of the time interval delta and f' is the dominant frequency of the audio input 205.

The motor speed ω may be based on a ratio of the magnitude of the spaced dominant frequency to the maximum magnitude of the spaced dominant frequency in the audio input 205:

wherein A is_δIs the amplitude A, A of the specific time interval delta_maxIs the maximum amplitude of the amplitude A determined for the portion 210 of the audio input 205, and ω is_maxIs the maximum rated rotational speed at which the motor 700 can rotate.

For example, at time interval delta_t1Of medium frequency f₂Is the interval dominant frequency. The frequency of the square wave may be proportional to the interval main frequency, in this case f₂And motor speed ω₁May be separated from the time interval delta_t1Amplitude A in₁And (4) in proportion. At a time interval delta_t2Of medium frequency f₁Is the interval dominant frequency. In the haptic mode 605, the frequency of the square wave may be spaced from the dominant frequency f₁Proportional and motor speed ω₂May be separated from the time interval delta_t2Amplitude A in₂And (4) in proportion. Time interval delta_t1Interval pattern (based on frequency f)₂) And will therefore be longer than the time interval delta_t2Is faster because of the frequency f₂Greater than frequency f₁. Alternatively or additionally, computer 105 and/or user device processor 155 may determine a plurality of haptic patterns based on a plurality of filtered audio inputs generated from a plurality of identified frequencies f, e.g., based on a second frequency band [ f [ ]₂-f^*，f₂+f^*]A second haptic pattern is determined for the base second filtered audio input.

Fig. 7 illustrates an example motor 700 that can be installed in the wearable device 140 and/or the user device 150 and actuated to output a haptic pattern 605. The motor 700 may include a shaft 705 and an eccentric weight 710 fixed to the shaft. The eccentric weights are asymmetric about the motor axis 715. When shaft 705 rotates eccentric weight 710, eccentric weight 710 may generate a centripetal force that vibrates motor 700 and wearable device 140. As described above, the wearable device processor 145 may be programmed to rotate the shaft 705 to output the haptic pattern 605, thereby generating a varying centripetal force that may be detected by the user.

Computer 105 and/or user device processor 155 may map haptic pattern 605 to an action. The action may be an event and/or condition that may require attention of the user. Once the action is recognized, the computer 105 and/or user device processor 155 may prompt the user by actuating the motor 700 to output the haptic pattern 605. The action may be, for example, data 115 of the vehicle component 120 that exceeds a threshold (e.g., speed of the vehicle 101, acceleration of the vehicle 101, etc.), a time of an appointment stored in a calendar, an arrival at a location stored in the data storage 106, etc. Because the haptic pattern 605 may be specific to the audio input 205, the user may identify a particular action based on the haptic pattern 605. Computer 105 and/or user device processor 155 may map multiple haptic patterns 605 to multiple actions.

Fig. 8 shows an exemplary process 800 for determining a haptic pattern 605 of a motor 700 in a wearable device 140. Process 800 begins at block 805 where computer 105 and/or user device processor 155 receives audio input 205. The audio input 205 may be, for example, a pre-recorded audio file, an input from a microphone in the user device 150, or the like. Computer 105 and/or user device processor 155 may receive user input identifying portion 210 of audio input 205. As described above, user device processor 155 may prompt the user to provide audio input 205 and/or identify portion 210 of audio input 205 through tactile input on a touch screen display of user device 150.

Next, in block 810, the computer 105 and/or user device processor 155 identifies the dominant frequency f 'and dominant frequency band [ f' -f 'of the audio input 205 based on the dominant frequency f' of the audio input 205^*，f′+f^*]. The computer 105 and/or user device processor 155 may identify the dominant frequency f' by applying known transform techniques (e.g., FFT) to the audio input 205 and determining the frequency of the amplitude maximum.

Next, in block 815, the computer 105 and/or user device processor 155 filters the audio input 205 with a band pass filter based on the primary frequency band. As described above, the band pass filter may remove frequencies from the audio input 205 that are outside the main frequency band.

Next, in block 820, the computer 105 and/or user device processor 155 identifies one or more time intervals δ based on the dominant frequency of the filtered audio input 205. As mentioned above, the time interval δ is based on the time value t when the amplitude of one main frequency is equal to the amplitude of the other main frequency.

Next, in block 825, the computer 105 and/or user device processor 155 identifies a gap dominant frequency for each time interval δ and identifies an amplitude a for each gap dominant frequency. As mentioned above, the interval dominant frequency is the dominant frequency during the time interval δ.

Next, in block 830, computer 105 and/or user device processor 155 maps haptic pattern 605. As described above, computer 105 and/or user device processor 155 maps haptic pattern 605 based on magnitude, interval dominant frequency, and dominant frequency. Each amplitude a may define a motor speed ω and pulse width for each time interval δ in the haptic pattern 605 of motor 700 rotation according to a square wave defined by the interval dominant frequency and amplitude.

Next, in block 835, computer 105 and/or user device processor 155 maps the action to haptic pattern 605. The action may be an event and/or condition that, when recognized, causes the computer 105 and/or user device processor 155 to prompt the user by actuating the motor 700 to output the haptic pattern 605. The action may be, for example, data 115 of the vehicle component 120 that exceeds a threshold (e.g., speed of the vehicle 101, acceleration of the vehicle 101, etc.), a time of an appointment stored in a calendar, an arrival at a location stored in the data storage 106, etc.

Next, in block 840, computer 105 and/or user device processor 155 recognizes that an action mapped to haptic pattern 605 has occurred. The computer 105 and/or the user device processor 155 may determine, based on the collected data 115 (e.g., speed data 115, location data 115, time data 115, etc.), that the action has occurred, e.g., the speed of the vehicle 101 has exceeded a speed threshold, it is time for an appointment, etc. The computer 105 and/or the user device processor 155 may communicate over the network 125 to determine that the action has occurred.

Next, in block 845, computer 105 and/or user device processor 155 instructs wearable device processor 145 to actuate motor 700 to output haptic pattern 605. Computer 105 and/or user device processor 155 may send haptic pattern 605 to wearable device processor 145 over network 125. The wearable device processor 145 can then actuate the motor 700 according to the haptic pattern 605. After block 845, the process 800 ends.

As used herein, the adverb "substantially" modifying the adjective means that shapes, structures, measurements, values, calculations, etc., may deviate from the precisely described geometries, distances, measurements, values, calculations, etc., due to imperfections in materials, processing, manufacturing, data collector measurements, calculations, processing time, communication time, etc.

Computers 105 typically each include instructions executable by one or more computing devices, such as those mentioned above, for performing the blocks or steps of the processes described above. The computer-executable instructions may be compiled or interpreted by a computer program created using various programming languages and/or techniques, including but not limited to Java, alone or in combination^TMC, C + +, Visual Basic, Java Script, Perl, HTML, and the like. Generally, a processor (e.g., a microprocessor) receives instructions, e.g., from a memory, a computer-readable medium, etc., and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein. Such instructions and other data may be stored and transmitted using a variety of computer-readable media. A file in computing device 105 is typically a collection of data stored on a computer-readable medium, such as a storage medium, random access memory, or the like.

Computer-readable media includes any medium that participates in providing data (e.g., instructions) that may be read by a computer. Such a medium may take many forms, including but not limited to, non-volatile media, and the like. Non-volatile media includes, for example, optical or magnetic disks and other persistent memory. Non-volatile media include Dynamic Random Access Memory (DRAM), which typically constitutes a main memory. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a flash EEPROM, any other memory chip or cartridge, or any other medium from which a computer can read.

With respect to the media, processes, systems, methods, etc., described herein, it should be understood that although the steps of such processes, etc., have been described as occurring according to some ordered sequence, such processes may be practiced with the described steps performed in an order other than the order described herein. It is also understood that certain steps may be performed simultaneously, that other steps may be added, or that certain steps described herein may be omitted. For example, in process 800, one or more steps may be omitted, or steps may be performed in a different order than shown in fig. 8. In other words, the description of systems and/or processes herein is provided to illustrate certain embodiments and should in no way be construed as limiting the disclosed subject matter.

Accordingly, it is to be understood that the disclosure, including the above description and drawings and the following claims, is intended to be illustrative and not restrictive. Many embodiments and applications other than the examples provided would be apparent to those of ordinary skill in the art upon reading the above description. The scope of the invention should be determined, not with reference to the above description, but should instead be determined with reference to the appended claims, and/or the full scope of equivalents to which such claims are entitled, including those claims included herein as interpreted in non-provisional patent application. It is contemplated and intended that future developments will occur in the arts discussed herein, and that the disclosed systems and methods will be incorporated into such future embodiments. In sum, it should be understood that the disclosed subject matter is capable of modification and variation.

The article "a" or "an" modifying a noun should be understood as one or more unless otherwise indicated herein or otherwise required by the context. The phrase "based on" encompasses being based in part or in whole.