System and method for vehicle occupant vital sign detection

Abstract

Methods and systems for detecting and / or estimating a rate of vital signs from an occupant within a cabin of a vehicle. In some implementations, the method may include using a plurality of different distance bins to identify a repeating pattern of Doppler spectrum peaks in the RADAR signal. The signal data may then be used to identify an estimated frequency distance between adjacent peaks of the repeating pattern. The estimated frequency distance may then be used to calculate an estimated rate of repetitive vital signs of an occupant within a cabin of the vehicle.

Description

SUMMARY OF THE INVENTION

[0001] RADAR is typically used to detect objects external to a vehicle, such as other vehicles, pedestrians, and obstacles. However, RADAR or other electromagnetic radiation signals are generally not emitted in the direction of the vehicle occupants in the cockpit, let alone used to monitor important conditions that may affect the safety of the occupants, such as respiratory rate, heart rate, or other vital signs.

[0002] Accordingly, the present inventors have determined that there is a desire to provide systems and methods that overcome one or more of the foregoing limitations and / or other limitations of the prior art. Accordingly, systems and methods for detecting and / or monitoring the vital signs of an occupant within a vehicle are disclosed herein.

[0003] Thus, in some embodiments, the inventive concepts disclosed herein can be used to detect the vital signs of one or more occupants within a vehicle, estimate the vital sign rates of such vital signs, classify vehicle occupants at least in part using such data, and / or take various actions using such data.

[0004] In a more specific example of a method for detecting occupant vital signs from within a vehicle cockpit using RADAR, the method can include identifying a repeating pattern of Doppler spectral peaks in RADAR signals across a plurality of different range bins. An estimated frequency distance between adjacent peaks of the repeating pattern (such as, in some cases, a repeating pattern within the same range bin) can then be identified. The estimated frequency distance can then be used to calculate an estimated rate of repeating vital signs of one or more occupants within the vehicle cockpit.

[0005] In some specific implementations, the estimated repeating vital signs can include respiratory rate. Alternatively, the estimated repeating vital signs can include, for example, heart rate.

[0006] In some specific implementations, the step of identifying a repeating pattern of Doppler spectral peaks can include selecting the strongest repeating signal from a plurality of RADAR signals. Some specific implementations can also include selecting one or more other signals that are sufficiently correlated with the strongest repeating signal. For example, some specific implementations can include selecting at least one range bin adjacent to the range bin associated with the strongest signal and identifying the estimated frequency distance between adjacent peaks of the repeating pattern from the RADAR signals in at least one range bin adjacent to the range bin associated with the strongest signal.

[0007] Some specific implementations can also include using the estimated frequency distance between adjacent peaks of the repeating RADAR signals in at least one range bin adjacent to the range bin associated with the strongest signal to improve the accuracy of at least one estimated parameter derived from the repeating RADAR signals.

[0008] In some specific implementations, the at least one estimated parameter may include the position of the occupant within the vehicle.

[0009] Some specific implementations may also include classifying the occupant using the estimated vital signs.

[0010] In an example of a method for detecting an occupant's vital signs from within a vehicle's cockpit, the method may include transmitting one or more electromagnetic signals within the vehicle's cockpit and processing signals associated with the one or more electromagnetic signals, such as signals reflected from the one or more electromagnetic signals. The distance between adjacent signal frequency peaks may be derived from the reflected signal, which may indicate the vital signs of an occupant within the vehicle's cockpit. The distance between adjacent frequency peaks may then be used to estimate the rate of the occupant's vital signs.

[0011] In some specific implementations of receiving the reflected signal, the step of processing the reflected signal may include processing the reflected signal of one or more electromagnetic signals from one or more range bins. As described throughout this disclosure, in some embodiments, this may be done by identifying the estimated frequency distance between adjacent Doppler peaks. In some such embodiments, the step of processing the reflected signal may include processing the reflected signal of one or more electromagnetic signals from a first range bin corresponding to a target range bin and a second range bin adjacent to the target range bin. Some embodiments may also include identifying the target range bin by comparing the signal strengths of the reflected signals.

[0012] In some specific implementations, each of the one or more electromagnetic signals may include a RADAR signal.

[0013] Some specific implementations may also include transmitting the one or more electromagnetic signals within the vehicle's cockpit in an expected direction corresponding to the desired position of the occupant. For example, after detecting a signal indicating possible vital signs, a RADAR or other electromagnetic sensor may be tuned to the position of the occupant associated with the signal.

[0014] In some specific implementations, the rate of the vital signs may include the respiratory rate. Alternatively, the rate of the vital signs may include the heart rate.

[0015] In an example of a system for detecting a vehicle occupant's vital signs using electromagnetic signals within a vehicle cabin, the system can include one or more electromagnetic sensors positioned within the vehicle cabin, such as a RADAR module. The system can also include a detection module and / or a vital signs module, the detection module being configured to process reflected electromagnetic signals into a plurality of range bins, the vital signs module being configured to use a signal repetition frequency associated with one or more of the range bins (such as a distance between adjacent frequency peaks) and estimate a rate associated with the vital signs of an occupant within the vehicle cabin.

[0016] Some embodiments can also include a classification module that can be configured to receive information from the vital signs module and classify the occupant according to an age group using the rate associated with the occupant's vital signs.

[0017] The vital signs module can be configured to estimate the breathing rate and / or heart rate of the occupant.

[0018] In some embodiments, the electromagnetic sensor can be configured to tune the signal to a target location expected to correspond to the position of the occupant.

[0019] Features, structures, steps, or characteristics disclosed in connection with one embodiment can be combined in any suitable manner in one or more alternative embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] With reference to the drawings, non-limiting and non-exhaustive embodiments of the present disclosure are described, including various embodiments of the present disclosure, wherein:

[0021] Figure 1 A vehicle including a system for detecting a vehicle occupant's vital signs is depicted according to some embodiments;

[0022] Figure 2 is a graph representing a Doppler spectral signal received from a vehicle occupant;

[0023] Figure 3 is a graph representing a series of signals, each signal in a different range bin, representing data from which a vehicle occupant's vital signs can be derived;

[0024] Figure 4 is a chart showing a statistical correlation (in breaths per minute) between age and breathing rate, which statistical correlation can be used to classify vehicle occupants according to a vital signs rate;

[0025] Figure 5 is a block diagram showing an example of a system for estimating a vehicle occupant's vital signs according to some embodiments;

[0026] Figure 6 depicts an example of a vehicle including a system for estimating the vital sign rate of an occupant in a vehicle; and

[0027] Figure 7 is a flowchart depicting an example of a method for using electromagnetic radiation to detect and estimate the vital signs of a vehicle occupant according to some specific implementations. DETAILED DESCRIPTION

[0028] It will be readily understood that, as generally described and illustrated in the figures herein, the components of the present disclosure can be arranged and designed in a wide variety of different configurations. Accordingly, the following more detailed description of the embodiments of the device is not intended to limit the scope of the invention, but merely represents possible embodiments of the invention. In some instances, well-known structures, materials, or operations are not shown or described in detail.

[0029] As used herein, the term "substantially" means the full or nearly full extent or degree to which an action, characteristic, property, state, structure, item, or result functions as indicated. For example, an object that is "substantially" cylindrical or "substantially" vertical will mean that the object / feature is cylindrical / vertical or nearly cylindrical / vertical, resulting in the same or nearly the same function. The exact allowable degree of deviation provided by this term can depend on the specific context. When used in a negative sense, "substantially" applies equally, referring to the complete or nearly complete lack of an action, characteristic, property, state, structure, item, or result. For example, a structure that is "substantially without" a bottom either completely lacks a bottom or nearly completely lacks a bottom such that its effect is substantially the same as completely lacking a bottom.

[0030] Similarly, the term "about" as used herein provides flexibility to the endpoints of a numerical range, i.e., a given value can be "slightly higher" or "slightly lower" than the endpoint while still achieving the function associated with the range.

[0031] The embodiments of the present disclosure can be best understood by reference to the accompanying figures, in which like components may be represented by like numerals. It will be readily understood that, as generally described and illustrated in the figures herein, the components of the disclosed embodiments can be arranged and designed in a wide variety of different configurations. Accordingly, the following detailed description of the embodiments of the device and method is not intended to limit the scope of the present disclosure (as claimed), but merely represents a representative illustration of possible embodiments of the present disclosure. Additionally, unless otherwise specified, the steps of a method need not be performed in any particular order, or even in sequence, nor need they be performed only once. Certain preferred embodiments and additional details of specific implementations will now be described in more detail with reference to the accompanying figures.

[0032] Figure 1Depicts a system 100 for detecting the vital signs of an occupant within the cockpit of a vehicle 105. As shown in the figure, one or more sensors may be positioned at various locations within the cockpit of the vehicle 105. In the depicted embodiment, the vehicle 105 includes three sensors 115, 120, and 125. Sensor 115 is positioned on one side of the vehicle 105, sensor 120 is positioned at a central location within the vehicle 105, such as mounted on the ceiling of the cockpit, and sensor 125 is mounted on the opposite side of the vehicle 105. However, as will be understood by those of ordinary skill in the art, a wide variety of alternative arrangements are possible, including different numbers of sensors, different types of sensors, and sensors located at different positions.

[0033] For example, in a preferred embodiment, sensors 115, 120, and 125 may include RADAR sensors, such as frequency-modulated continuous-wave (FMCW) ultra-wideband RADAR sensors configured to operate at 60 GHz. However, in alternative embodiments, other types of sensors may be used, such as LIDAR or other types of electromagnetic sensors. Additionally, in some embodiments, a single sensor, such as sensor 120, may be used, or two sensors (e.g., one in the middle of the vehicle and one only on one side of the vehicle). More than three sensors may also be used in some embodiments. Although the sensors may preferably be positioned in the roof / ceiling or the upper side of the vehicle pillars, in some such embodiments, or in alternative embodiments with three or fewer sensors, for example, such sensors may alternatively be positioned in the front of the vehicle, the rear of the vehicle, within the seats of the vehicle, and / or the floorboard of the vehicle.

[0034] As indicated by the various lines extending from sensors 115 / 120 / 125, each of these sensors may be configured to transmit electromagnetic signals into and / or receive electromagnetic signals from a particular region of the cockpit of the vehicle 105, preferably so as to be able to at least detect an occupant within each seat of the vehicle 105. Of course, again, those of ordinary skill in the art may envision and / or obtain many alternative arrangements after obtaining the benefits of this disclosure. For example, for some vehicles, a single sensor positioned in the appropriate location may be sufficient to adequately detect the occupants in each seat of the vehicle. Similarly, in other embodiments, it may be desirable to provide dedicated RADAR or other electromagnetic sensors for each seat of the vehicle.

[0035] As described in more detail below, regardless of the placement, number, and type of electromagnetic sensors used in a vehicle, in a preferred embodiment, such sensors can be used to identify one or more occupants present in the cockpit and to identify vital sign data regarding such occupants. The vital sign data, such as respiratory rate, tidal volume variation, and / or heart rate, can, for example, be used to classify the occupants. For example, vehicle occupants can be classified according to their age group. By doing so, various actions and / or changes to vehicle functions can be taken based on the classification and / or location of the vehicle occupants.

[0036] Vital sign data can be collected, for example, using RADAR frequency response data from the vital signals of the occupants. To provide an example of a model for tracking vital sign signals, consider the following formula:

[0037] · s(t) = A(t)e jφ(t) ; A(t) is the target amplitude

[0038] · r0 is the target nominal distance.

[0039] · r(t) = b sin ω0t ;; r(t) is the target motion over time, and b is the maximum motion of the target

[0040] · δ(t): phase noise

[0041] Then, the frequency domain representation of the vital sign signal can be expressed as follows:

[0042] · where J -n is the Bessel first integral, and

[0043] Figure 2 is a graph representing the Doppler spectrum signal received from an adult occupant of the vehicle. In the example provided in the figure, it is estimated that the adult has a respiratory rate of approximately 10.15 breaths per minute. As shown in the graph, using the above formula, the respiratory rate can be derived from the distance between the peaks in the signal or "repetition frequency", and several of these peaks are circled in the graph.

[0044] Figure 3 is another graph representing a series of signals, each signal in a different range bin. Each range bin represents a distance of approximately 0.047 m from the sensor, and each frequency bin represents a frequency band of approximately 0.078 Hz. Figure 2 The signal shown on the graph of Figure 3 is represented in range bin 22 of the graph of Figure 3 and is the strongest signal detected among those signals shown in

[0045] The Doppler spectral peak is represented by a point in the graph of Figure 3 and, again, some of these peaks are circled. This represents the Doppler spectral peaks that exceed the detection threshold. In this example, only two Doppler peaks are allowed per range bin. The frequency repetition indicated by the parentheses adjacent to range bin 47 can similarly be derived from the Figure 3 frequency spread shown in. Note that signals from other range bins typically have the same frequency repetition rate, which can be attributed to other regions of the same occupant's body or from multipath propagation. Of course, some signals can be distinguished as coming from different occupants or other objects within the vehicle. One of ordinary skill in the art will appreciate that such signals can be processed and / or extracted through processing and / or filtering steps disclosed herein or available to one of ordinary skill in the art to identify the signal.

[0046] As described above, although the Figure 2 and Figure 3 data shown in represent the respiratory rate, similar techniques can be used to estimate other vital signs. For example, the estimated heart rate and / or tidal volume changes can alternatively be derived from RADAR or other electromagnetic signals using the methods disclosed herein.

[0047] Once the respiratory rate or other vital signs are estimated for one or more occupants within the vehicle using RADAR or other electromagnetic signal processing techniques, this vital sign data can be used to classify the occupants. For example, since the respiratory rate is strongly correlated with age, the estimated respiratory rate derived from RADAR signal processing can be used to estimate the age of the occupant.

[0048] Figure 4 is a graph showing the statistical correlation between age and respiratory rate in breaths per minute. The graph shows how a respiratory rate of, for example, approximately 40 breaths per minute can reasonably be used to classify an occupant as an infant. Thus, using statistical data such as from the Figure 4 graph or other similar data, the vehicle can be configured to use the respiratory rate or other vital sign rate to classify the occupants according to the predicted age group of the occupants. As described in more detail below, this classification can then be used by the vehicle in various ways to perform useful functions.

[0049] For example, if a passenger is identified as an infant, the airbag in the seat associated with that occupant can be automatically disabled. As another example, if an occupant is identified as an infant or child and remains in the vehicle after the vehicle has been turned off and / or the driver of the vehicle has left the cockpit, the vehicle can be configured to send a notification or warning about the left-behind occupant. In some embodiments, the vehicle can be configured to continue monitoring the remaining occupants in the vehicle and provide such a notification only in the event of a data convergence, which data can include data from other sensors.

[0050] For example, rather than immediately sending a notification if the vital sign data from a RADAR or other electromagnetic sensor has classified an occupant as an infant or child, the vehicle can be configured to monitor other data, such as the temperature and / or time since the child has been left in the vehicle. For example, upon detecting that the temperature inside the cockpit exceeds a threshold temperature (such as 90 degrees Fahrenheit), in combination with data indicating that a child has been left in the vehicle, the vehicle can be configured to send a notification to the user. The warning can be sent, for example, to the smart phone of the vehicle owner / user. Alternatively, the vehicle can be configured to automatically start the engine and / or activate the vehicle's air conditioning unit in response to the detection of these triggers / thresholds. It should be understood that in some embodiments, any one of the sensors 115 / 120 / 125 can thus include a temperature sensor that can operate in conjunction with a RADAR or other electromagnetic sensor to achieve this result.

[0051] Figure 5 is a block diagram illustrating an example of a system 510 for estimating the vital signs of an occupant within a vehicle according to some embodiments. As shown in this figure, a detection list including one or more detected signals from a RADAR or other electromagnetic sensor can be fed into bins such as range bins.

[0052] At 512, Figure 5 indicates that the system can be configured to identify a target signal from the detection list, such as a target range bin or other data set associated with a target and / or target range. In some embodiments and implementations of the associated method, this can be done by identifying the strongest signal and / or range bin signal from the detection list available in the detection structure and having a repeating pattern indicative of vital signs. Thus, referring back to Figure 3 the chart (which can be considered an example of a "detection list" for the purpose of Figure 5 ), the detection in range bin 22 can be identified as the target signal or target bin at 512.

[0053] The target signal data (including data collected and / or processed before and / or after the identification of the target signal / target bin) can then be used to obtain and refine the Doppler frequency spread spectrum. Thus, for example, the target signal data can be used to identify the Doppler spectrum peak location, as indicated at 511.

[0054] In some embodiments and implementations, the fast Fourier transform (FFT) method can be used to process the data and output an estimated vital sign. Thus, a buffer distance for the FFT data can be provided, also as Figure 5 indicated therein. In some such embodiments and implementations, the buffered distance FFT data can be the data of the past N frames (e.g., N can be equal to 128 frames). In some cases, the data can be associated with a specific target location corresponding to the vehicle occupant whose vital sign is being monitored. Thus, multiple sets of data can be used, each set corresponding to a different occupant. Alternatively, of course, the system 510 can be configured to simply detect the presence of a vehicle occupant without considering the position of the occupant.

[0055] In some embodiments and implementations, the system 510 can be configured to improve the accuracy of the distance at 514. This can include, for example, using interpolation techniques or other similar techniques available to those of ordinary skill in the art, such as, for example, an interpolation technique using a first estimator and a second estimator of Quinn.

[0056] In some embodiments and implementations, a Doppler FFT can be performed, as indicated at 516 in Figure 5 the same. This can be performed for the target range bin / dataset, and in some preferred embodiments, can also be performed for one or more range bins / datasets adjacent to or otherwise sufficiently related to the target range bin / dataset to improve the vital sign estimation. For example, in some embodiments, each target range bin / dataset within a specific number of bins of the target range bin can be used. Alternatively, each dataset within a threshold signal strength of the target range bin / data can be used.

[0057] In some embodiments and implementations, cross-channel processing may be performed at 518, preferably on all received signal channels that are associated with the target range bin / dataset and / or adjacent to or otherwise sufficiently related to the target range bin / dataset. This may be achieved, for example, by averaging all received channel signals and / or performing cross-channel processing. Alternatively, this may be achieved by beamforming the signal to an expected direction, which may be determined after the position of the occupant within the vehicle and / or initial signal processing to determine a more precise position associated with a particular occupant to improve signal strength, such as a particular part of the occupant's chest for respiration rate estimation or a particular part of the occupant's heart for heart rate estimation.

[0058] At 521, the data from the cross-channel processing may then be used to estimate current vital signs, such as the current respiration rate. In some embodiments and implementations, this may be achieved by determining the frequency peak distance in the signal dataset associated with the target range bin / target dataset, as indicated at 523. Thus, for example, the Doppler spectral peaks in the target range bin and / or target signal dataset of interest may be identified and / or stored at 522. The Doppler spectral peaks may then be filtered at 524, which may allow the estimation of the frequency distance or average frequency distance between adjacent peaks in at least a portion of the spectrum or spectrum / dataset, as indicated at 526.

[0059] The frequency distance between adjacent peaks in the dataset may then be used to calculate the estimated respiration rate or another vital sign for all range bins or other data sets of interest, as indicated at 528. In some embodiments, in some cases over a pre-determined time period, the rate associated with the vital sign may be calculated / estimated by calculating the average / mean, weighted mean, or median distance between adjacent Doppler spectral peaks in each of the range bins / data sets of interest.

[0060] Then, at 532, each of the various respiration rates or other vital signs for each bin in the bin or other data sets may be combined into a single current vital sign. Again, this may be achieved by using the target range bin / data set or the target range bin / data set and a number of adjacent or otherwise sufficiently related range bins / data sets, as previously mentioned. For example, the current vital sign may be processed as a rolling average / mean, weighted mean, or median over a pre-determined time period.

[0061] In some embodiments and implementations, the respiration rate or other vital sign may be filtered at 534 before being sent to another module and / or component of the vehicle, for example, as in Figure 5As pointed out in. This can be achieved, for example, using filters such as alpha filters, Kalman filters, etc. The resulting vital sign data can then be used to take various actions and / or parameter changes, as described in more detail below.

[0062] Figure 6 An example of a system 600 for estimating the vital signs of an occupant in a vehicle 605 is shown. System 600 can include an internal system 610, which can combine various combinations of hardware, software, firmware, etc. as needed. System 600 includes a first sensor module 615 and a second sensor module 620. Those of ordinary skill in the art will understand that although two sensors / sensor modules are shown in the depicted embodiment, the number of sensors can vary as needed without departing from the main inventive principles of system 610, including a single sensor or more than two sensors.

[0063] The first sensor module 615 and the second sensor module 620 can include any number of sensors as needed, such as RADAR sensors, LIDAR sensors, or other sensors configured to transmit and / or receive electromagnetic radiation. Sensor modules 615 and 620 can also include various other software, hardware, and / or firmware elements as needed to send and receive signals for processing by other modules. Although the preferred embodiment may include and / or be limited to electromagnetic radiation sensors, it is contemplated that in some embodiments, sensors 615, 620, and 625 can include any other sensors as needed, such as, for example, scale / weight / pressure sensors, temperature sensors, etc.

[0064] System 610 also includes a controller 630, which can be configured to process data from sensor modules 615 / 620. As used herein, the term "controller" refers to a hardware device that includes a processor and preferably also includes a memory element. The memory can be configured to store one or more of the modules mentioned herein, and controller 630 and / or one or more processors can be configured to execute these modules to perform one or more processes as described herein.

[0065] System 610 also includes a detection module 640 coupled to both sensor modules 615 / 620. Of course, in some embodiments, if desired, an independent detection module can be provided for each sensor and / or sensor module. The detection module 640 can be configured to receive raw, sensed data from the sensors of sensor modules 615 / 620 and attempt to identify / detect an occupant within vehicle 605 by using such data (such as by detecting evidence of breathing or another vital sign), as described above and throughout this disclosure. Although in a preferred embodiment, system 610 can be configured to specifically detect human occupants, it is contemplated that the principles herein can also be used to detect other living occupants of the vehicle, such as dogs, cats, or other pets.

[0066] The detection module 640 can be communicatively coupled to a vital signs module 650. The vital signs module 650 can be configured to process incoming data to identify the vital signs (such as respiratory rate or heart rate) of the occupant and estimate that rate, as described above. Thus, in some embodiments, the vital signs module 650 can be configured to perform Figure 5 each or at least one subset of the steps / processes in system 510, as described in detail above. The resulting vital signs can then be used by system 610 to modify one or more features / parameters of vehicle 605 and / or otherwise act based on such data.

[0067] In some embodiments, this data can be used by a classification module 660 to classify vehicle occupants associated with a particular estimated vital sign. Of course, in some embodiments, the classification module 660 can be configured to classify each occupant within vehicle 605 based on independent vital signs associated with each vehicle occupant. As an example of a useful classification based at least in part on respiratory rate or other vital signs, the classification module 660 can be configured to classify an occupant as an infant, child, and / or adult. In some embodiments, for example, the classification module 660 can be configured with one or more predetermined ranges of respiratory rate or other respiratory rates based on statistics associating age with such vital signs (such as Figure 4 the data depicted in).

[0068] In some embodiments, the classification module 660 can be configured to classify an occupant using solely a statistical analysis of the incoming vital signs data. Alternatively, other parameters and / or features can be used in combination with parameters / features derived from the statistical analysis (such as data indicative of the stature / weight of the occupant), which can also be derived from the same RADAR sensor or other electromagnetic radiation data. Alternatively, such data can be obtained from other sensors (such as weight sensors, temperature sensors, cameras, etc.). Thus, it should be understood that, for example Figure 6The term sensor herein should be considered to include such other sensors in some contemplated embodiments. However, it should also be understood that in some preferred embodiments, the term may be limited to electromagnetic sensors, such as RADAR sensors.

[0069] Figure 7 is a flowchart depicting an example of method 700 for detecting and estimating the vital signs of vehicle occupants using electromagnetic radiation according to some specific implementations. Method 700 may begin with the transmission 705 of various electromagnetic signals (such as RADAR signals) from one or more sensors as described above. In some specific implementations, these signals may be transmitted to a specific location corresponding to a seat of the vehicle, multiple sensors may be used for beamforming, or they may be more widely distributed throughout the vehicle in order to detect possible occupants located elsewhere in the vehicle. Also, a single sensor may be used to send signals to multiple seats / locations, or multiple sensors may be used as needed. For example, an independent sensor may be used for each seat, an independent sensor may be used for each row of the vehicle, or one or more sensors may be positioned from one lateral side of the vehicle to the other along the central portion of the vehicle, as Figure 1 shown.

[0070] The signals may then be received and / or processed at 710. In some specific implementations, these signals may include reflected signals, but this need not be the case for all contemplated specific implementations. Instead, in some specific implementations, step 710 may include receiving at a second sensor a signal transmitted from a first sensor.

[0071] The repetition frequency may then be identified at 715. As previously described, in some embodiments, this may be achieved by identifying peaks in the Doppler spectrum associated with one or more range bins and / or data sets. For example, RADAR data may be binned based on, for example, range or any other suitable parameter, and then one or more signals having the strongest recognizable repeating peak pattern may be identified and processed.

[0072] Such processing can be used to estimate vital signs at 720. For example, as described above and throughout this disclosure, vital signs can be associated with a repeating signal pattern and / or a particular occupant, and then the distance between adjacent peaks in the pattern, or a statistical analysis of such a pattern, such as the distance between adjacent peaks and / or interpolation, mean, weighted mean, and / or median of an initial vital sign rate estimate, can be used to determine and / or refine the vital sign estimate. In some specific implementations, additional processing steps, such as applying a smoothing filter to the vital sign estimate, can also occur as part of step 720. Preferably, the vital sign estimate is then processed and improved over time to maintain a real-time or at least substantially real-time estimate of the vital signs of one or more occupants in the vehicle.

[0073] Once a vital sign estimate has been obtained, which can be done in step 720 or, in some specific implementations, based on an initial estimate of the repetition frequency of step 715, the vital sign estimate can be used to at least partially classify one or more occupants of the vehicle, as indicated at 725 in method 700. For example, in some specific implementations, vehicle occupants can be classified based on a predicted age group of the vehicle occupant, which can be based entirely or at least partially on the vital sign estimate. This can involve the use of vital sign thresholds and / or vital sign ranges. For example, if the detected respiratory rate is at least 30 breaths per minute, the associated vehicle occupant can be classified as a child. In some specific implementations, the classification may require a stable rate detection, such as an estimate within a threshold and / or range over a predetermined time period, in order to prevent a temporary increase in the respiratory rate or another vital sign from reclassifying the occupant.

[0074] Occupants can also be classified based on thresholds associated with an older, rather than younger, age and / or a health condition that may be associated with a particular vital sign and / or vital sign rate. For example, if a sufficiently low and preferably stable respiratory rate or other vital sign is detected, the occupant can be classified as an elderly person.

[0075] As another example of a possible classification based at least in part on a rate associated with a vital sign estimated using RADAR or another electromagnetic wave signal, in some embodiments and implementations, an occupant may be classified based on a detected change in a vital sign. For example, if a respiration rate, a heart rate, or another detected vital sign drops by a pre-determined amount, such as a pre-determined percentage or a pre-determined raw number of breaths / heartbeats per minute in a relatively simple example, the occupant may be classified as sleeping or in some other notable condition. In some embodiments and implementations, the method / system may be configured to perform this classification only for the driver, as other occupants sleeping may not need attention. Some embodiments and implementations may also or alternatively be configured to detect a threshold increase in a vital sign over time, which may be used to classify an occupant as experiencing a panic attack or some other notable condition.

[0076] Some vehicles / systems / methods may then be configured to take automatic actions at 730 based on vehicle occupant classification and / or reclassification. For example, some vehicles may be configured to automatically disable airbags associated with seats in which an occupant has been classified as a child / infant and / or in which an occupant vital sign cannot be detected.

[0077] Similarly, some implementations and embodiments may be configured to monitor for the presence or absence of an occupant and take one or more actions at least in part based thereon, which may be considered within the scope of various contemplated implementations of method 700. For example, after classifying an occupant as a child or infant, when it is detected that the vehicle has stopped, been turned off, and / or the driver and / or other occupants have left the vehicle, in some cases, after a threshold time period, the vehicle may be configured to send a warning / notification, turn on an air conditioning unit or heater, and / or notify a relevant agency when it is detected that a child has been left in the vehicle. In some cases, the warning / notification / action may occur only when other conditions (e.g., a high enough or low enough temperature) are detected. Similarly, in some cases, the warning / notification / action may occur only after a long enough time period has elapsed since the child left. However, depending on the estimated age, temperature, and / or other conditions of the occupant, this time period may be reduced or eliminated. The time, temperature, and / or other conditions required to trigger the warning / notification / action may be adjusted based on the expected age of the occupant. For example, the threshold time value and / or temperature from room temperature required to trigger the warning / notification / action may decrease as the expected age of the occupant decreases.

[0078] As another example, some vehicles / systems / methods can be configured to automatically take action based on detected changes in vital signs, such as a sufficiently sharp increase or decrease in vital signs. Such actions can include, for example, triggering a warning / notification / action within the vehicle or to a device away from the vehicle, such as a smart phone. In some embodiments, if a sharp increase or decrease in vital signs or another vital sign condition indicating danger is detected, the vehicle can be configured to take over control from the driver (or, in the case of an autonomous vehicle, simply reconfigure the current driving instruction set) to slow down, pull the vehicle over, and / or stop the vehicle.

[0079] As another example, in some embodiments and implementations, if a vital sign or vital sign change indicates a problem condition, such as an elderly occupant or one or more health conditions, the vehicle can be configured to enhance the monitoring of the vital sign, for example, by adjusting the RADAR to more specifically and / or closely monitor that vital sign and / or other vital signs of the vehicle occupant associated with the problem vital sign. In some cases, the vehicle can be configured to additionally or alternatively target other monitoring systems, sensors, etc. at a specific occupant of interest.

[0080] For example, to assist in monitoring possible health conditions or other conditions regarding the safety of vehicle occupants, the detection of a specific vital sign or vital sign change associated with a specific occupant (again, the driver of the vehicle may be guaranteed more attention and thus less strictly required to trigger a warning / action than other occupants) can trigger the actuation of another sensor and / or monitor within the vehicle, such as a camera.

[0081] As another example, for safety reasons, a vehicle can be configured to detect the presence of an unexpected occupant, such as detecting a vital sign where no vital sign is expected. For example, if the vehicle has been turned off, the engine has been turned off, or the vehicle has been locked, but has not been subsequently unlocked and / or properly restarted, the vehicle can be configured to monitor vital signs, and when a vital sign is detected in these or other situations where no vital sign is expected to be present, the vehicle and / or associated application and / or system can be configured to report the event to the vehicle owner and / or the police or other appropriate agency to provide enhanced security.

[0082] As yet another example, some embodiments and implementations can be configured to specifically identify the vital signs of non-human organisms, or in some cases, the vital signs of humans below a certain threshold age, either in conjunction with the vital signs of non-humans or as an alternative. When the presence of such non-human occupants (such as dogs, cats, or other pets) and / or human occupants who are expected to be unable to open the door or take care of themselves is detected, the vehicle can be configured to provide protection to such occupants. Similarly, such protection can be provided by offering automatic temperature regulation, which can be paired with temperature sensing to ensure that an appropriate temperature is maintained within the vehicle to protect such occupants. Alternatively or in addition, such protection can be provided by offering suitable notifications, warnings, etc., which can be provided to the vehicle owner / operator, such as via a mobile application on a smart phone, a notification to a relevant agency, etc.

[0083] In some embodiments and implementations, the vital sign detection data can be fused with data from other types of sensors (such as cameras or any other sensors available to those of ordinary skill in the art) to further verify and confirm the detection of a particular living occupant (whether human or otherwise) within the vehicle.

[0084] As used herein, a software module or component can include any type of computer instruction or computer-executable code located within a memory device and / or a machine-readable storage medium. For example, a software module can include a physical or logical block of one or more computer instructions, which can be organized as routines, programs, objects, components, data structures, etc. that perform one or more tasks or implement a particular abstract data type.

[0085] In certain embodiments, a particular software module can include different instructions stored in different locations within a memory device, which together implement the stated functionality of the module. In fact, a module can include a single instruction or multiple instructions, and can be distributed across multiple different code segments, different programs, and multiple memory devices. Some embodiments can operate in a distributed computing environment, in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, software modules can be located in local and / or remote memory storage devices. Additionally, data bound or combined in database records can reside within the same memory device or be distributed across multiple memory devices, and can be linked together in the fields of database records via a network.

[0086] In addition, the embodiments and specific implementations of the present invention disclosed herein may include various steps, which may be embodied in machine-executable instructions executed by a general-purpose or special-purpose computer (or another electronic device). Alternatively, the steps may be executed by hardware components including specific logic for executing the steps, or by a combination of hardware, software, and / or firmware.

[0087] The embodiments and / or specific implementations may also be provided as a computer program product, which includes a machine-readable storage medium having stored thereon instructions that can be used to program a computer (or other electronic device) to execute the processes as described herein. The machine-readable storage medium may include, but is not limited to: hard disk drives, floppy disks, optical disks, CD-ROMs, DVD-ROMs, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, solid state memory devices, or other types of media / machine-readable media suitable for storing electronic instructions. Memory and / or data storage may also be provided, which in some cases may include a non-transitory machine-readable storage medium containing executable program instructions configured to be executed by a processor, controller / control unit, etc.

[0088] The foregoing specification has been described with reference to various embodiments and specific implementations. However, those of ordinary skill in the art will understand that various modifications and changes can be made without departing from the scope of the present invention. For example, depending on the specific application or any cost function associated with the operation of the system, the various operation steps and the components for performing these operation steps can be implemented in a variety of ways. Thus, any one or more steps may be deleted, modified, or combined with other steps. In addition, the present disclosure should be considered illustrative rather than restrictive, and all such modifications are intended to be included within its scope. Similarly, the benefits, other advantages, and solutions to problems have been described above with respect to various embodiments. However, the benefits, advantages, solutions to problems, and any element that may cause any benefit, advantage, or solution to occur or become more pronounced should not be construed as critical, essential, or fundamental features or elements.

[0089] Those of ordinary skill in the art will understand that many changes can be made to the details of the above-described embodiments without departing from the basic principles of the present invention. Therefore, the scope of the present invention should be determined only by the following claims.

Claims

1. A method for detecting an occupant's vital signs from within a vehicle's cockpit using RADAR, the method comprising the steps of: Identify repeating patterns of Doppler spectral peaks in RADAR signals across multiple different range bins; Identify an estimated frequency separation between adjacent peaks of the repeating pattern; And Use the estimated frequency separation to calculate an estimated rate of repeating vital signs of an occupant within the vehicle's cabin.

2. The method according to claim 1, wherein the estimated repetitive vital signs include a respiration rate.

3. The method according to claim 1, wherein the estimated repetitive vital signs include a heart rate.

4. The method according to claim 1, wherein the step of identifying a repetitive pattern of Doppler spectral peaks comprises: Select the strongest repeating signal from a plurality of RADAR signals.

5. The method according to claim 4, the method further comprising: Select at least one range bin adjacent to the range bin associated with the strongest signal; And Identify an estimated frequency separation between adjacent peaks of a repeating pattern from RADAR signals in the at least one range bin adjacent to the range bin associated with the strongest signal.

6. The method according to claim 5, the method further comprising: Use the estimated frequency separation between adjacent peaks of the repeating RADAR signals in the at least one range bin adjacent to the range bin associated with the strongest signal to improve the accuracy of at least one estimated parameter derived from the repeating RADAR signals.

7. The method according to claim 6, wherein the at least one estimated parameter includes the position of the occupant within the vehicle.

8. The method according to claim 1, the method further comprising: Classify the occupant using the estimated repeating vital signs.

9. A method for detecting an occupant's vital signs from within a vehicle's cockpit, the method comprising the steps of: Transmit one or more electromagnetic signals within the vehicle's cabin; Process signals associated with the one or more electromagnetic signals; Identify a signal repetition frequency from the signals associated with the one or more electromagnetic signals, wherein the signal repetition frequency indicates the vital signs of an occupant within the vehicle's cabin; And Use the signal repetition frequency to estimate the vital signs of the occupant.

10. The method according to claim 9, wherein the signal associated with the one or more electromagnetic signals includes a reflected signal, and wherein the step of processing the reflected signal comprises: Process reflected signals of the one or more electromagnetic signals from multiple range bins.

11. The method according to claim 10, wherein the step of processing the reflected signal comprises: Process reflected signals of the one or more electromagnetic signals from a first range bin corresponding to a target range bin and a second range bin adjacent to the target range bin.

12. The method according to claim 11, the method further comprising: Identify the target range bin by comparing the signal strengths of the reflected signals.

13. The method according to claim 9, wherein the one or more electromagnetic signals include RADAR signals.

14. The method according to claim 9, the method further comprising:Transmit one or more electromagnetic signals within the vehicle's cabin in an expected direction corresponding to a desired position of an occupant.

15. The method according to claim 9, wherein the vital sign includes a respiration rate.

16. A system for detecting an occupant's vital signs inside a cockpit using electromagnetic signal processing, the system comprising: An electromagnetic sensor disposed within the vehicle's cabin; A detection module configured to process reflected electromagnetic signals into multiple range bins; And A vital signs module configured to use a signal repetition frequency associated with one or more of the range bins and estimate a rate associated with the vital signs of an occupant within the vehicle's cabin.

17. The system according to claim 16, wherein the electromagnetic sensor includes a RADAR sensor.

18. The system according to claim 16, the system further comprising a classification module configured to receive information from the vital sign module and classify the occupant according to age groups using the rate associated with the occupant's vital signs.

19. The system according to claim 16, wherein the vital sign module is configured to estimate the respiration rate of the occupant.

20. The system according to claim 16, wherein the electromagnetic sensor is configured to tune the signal to a target position expected to correspond to the position of the occupant.

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