Abstract:
Detecting and classifying rodent movement and/or motion includes sensing a first signal from a first sensor indicative of motion of a first rodent, wherein the first signal includes a first noise component and sensing a noise reference signal from a second sensor indicative of ambient noise. Next, modifying the first signal based on the noise reference signal to produce a first output signal, wherein said first output signal includes a second noise component less than the first noise component; and then outputting the first output signal.

Description:
BACKGROUND 
       [0001]    The present invention relates generally to monitoring rodents and, more particularly, to tracking rodent behavior in high throughput systems. 
         [0002]    Invasive techniques for qualifying animal behavior as either sleeping or awake are known such as Electroencephalographic (EEG) and Electromyographic (EMG) recordings. However, the surgery, surgery recovery, and signal scoring, among a number of other factors, limit their application to relatively small-scale studies. 
         [0003]    Non-invasively tracking rodent behavior in high throughput systems typically used in research laboratories with mice can include a number of difficulties as well. One challenge is to maintain reasonable costs that allow scaling up to multiple units while also maintaining reasonable accuracy. As an example, a non-invasive high throughput system for automatically detecting characteristic behaviors in mice over extended periods of time can be helpful for phenotyping experiments. A conventional tracking system can, for example, classify time intervals on the order of two to four seconds as corresponding to motions consistent with activity associated with an animal being awake or with inactivity associated with the animal sleeping. 
         [0004]    One typical sensor for detection movement is a single Polyvinylidine Difluoride (PVDF) sensor on a cage floor that generates electrical signals in response to pressure caused by movement of an animal. One difficulty with PVDF sensors is that they tend to be susceptible to noise from external sources such as electromagnetic interference (EMI), electro static noises from nearby moving bodies, light, and ambient vibrations. This susceptibility to noise can adversely impact a sensor&#39;s accuracy for detecting animal behaviors tied to low level signals such as those that result from sleeping, resting, REM sleep, NREM sleep, breath rates, etc. 
       SUMMARY 
       [0005]    Embodiments of the present invention relate to a method for detecting and classifying rodent movement and/or motion includes sensing a first signal from a first sensor indicative of motion of a first rodent, wherein the first signal includes a first noise component and sensing a noise reference signal from a second sensor indicative of ambient noise. Next, modifying the first signal based on the noise reference signal to produce a first output signal, wherein said first output signal includes a second noise component less than the first noise component; and then outputting the first output signal 
         [0006]    A system for detecting rodent movement that includes a first sensor configured to sense a first signal indicative of motion of a first rodent, wherein the first signal includes a first noise component; and a second sensor configured to sense a noise reference signal indicative of ambient noise. The system also includes a signal mixer configured to modify the first signal based on the noise reference signal to produce a first output signal, wherein said first output signal includes a second noise component less than the first noise component; and a signal transmitter configured to output the first output signal. 
         [0007]    It is understood that other embodiments of the present invention will become readily apparent to those skilled in the art from the following detailed description, wherein it is shown and described only various embodiments of the invention by way of illustration. As will be realized, the invention is capable of other and different embodiments and its several details are capable of modification in various other respects, all without departing from the spirit and scope of the present invention. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not as restrictive. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0008]    Various aspects of the present invention are illustrated by way of example, and not by way of limitation, in the accompanying drawings, wherein: 
           [0009]      FIG. 1  depicts a block-level diagram of an animal sensing system in accordance with the principles of the present invention. 
           [0010]      FIG. 2A  depicts a block level diagram of acquiring sensor signals in accordance with the principles of the present invention. 
           [0011]      FIG. 2B  depicts a flowchart of an exemplary method for performing noise cancellation in accordance with the principles of the present invention. 
           [0012]      FIG. 3  depicts details of an exemplary noise cancellation algorithm in accordance with the principles of the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0013]    The detailed description set forth below in connection with the appended drawings is intended as a description of various embodiments of the invention and is not intended to represent the only embodiments in which the invention may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention may be practiced without these specific details. In some instances, well known structures and components are shown in block diagram form in order to avoid obscuring the concepts of the invention. 
         [0014]    In the description below, reference is made to a PVDF sensor by way of example only and one of ordinary skill will recognize that other functionally equivalent sensors can be used without departing from the scope of the present invention. 
         [0015]      FIG. 1  depicts a block-level diagram of an animal sensing system in accordance with the principles of the present invention. At the most general level, the system  100  includes a cage  102  for a rodent, for example, that has a sensor  104  for detecting motion of the rodent such as a PVDF sensor. There is also a second, similar sensor  124  which is nearby but isolated from the sensor  104 . As explained below, the signals from the sensor  104  and from the sensor  124  can be combined in such a way as to improve the accuracy of sensing motion of the rodent. The term “nearby” can vary in meaning but is intended to encompass an area of proximity wherein the sensor  104  and  124  are exposed to substantially similar ambient conditions (e.g., light, electrical fields, vibration, noise, etc.). 
         [0016]    The cage  102  can have a floor to which the sensor  104  is coupled with such that rodent-caused vibrations within the cage  102  transmitted to the sensor  104 . The cage  102  and the sensor  104  can rest on a base  108  as well. In addition, a rubber pad, or isolation pad  106 , can be located between the sensor  104  and the base  108 . The base  108  can be sized and constructed such that electronic circuitry such as signal filters and amplifiers  110  can be located therein. This circuitry  110  can be connected to the sensor  104 . 
         [0017]    In the above-described environment, a rodent in the cage  102  will move (e.g., through breathing, or walking, or grooming, or sleeping) and cause the sensor  104  to generate a signal indicative of the motion of the rodent. This signal is then communicated through the connection  112 , which can be a wired or wireless connection, to the amplifier circuitry  110 . The resulting amplified signal  116  can then be communicated to a data acquisition and collection system  114 . 
         [0018]    The sensor signal (and amplified signal  116 ) may, however, have unwanted noise components that are not due to the motion of the rodent. For example, electrodes on the sensor  104  may pick up 60 Hz and other noises with aliased harmonics through electric fields. Nearby motion of other objects or individuals can create capacitive coupling within the sensor that results in low frequency transient noise. Also, ambient room vibrations can be coupled to the sensor  104  through the cage  102  and base  108 . 
         [0019]    Accordingly, in accordance with the principles of the present invention, a second, separate sensor  124  is arranged similar to the sensor  104 . The sensor  124  lays over an isolation pad  122  on a base  120  that houses a second set of amplifier circuitry  126 . The sensor  124  and amplifiers  126  communicate over a link  128 . A separate signal  130  produced by the second set of amplifier circuitry  126  is communicated to the data acquisition and collection system  114 . A difference between the sensor  104  and the sensor  124  is that the sensor  124  is not placed in a way such that it is coupled with a rodent&#39;s cage to sense motion of that rodent. However, the signal produced by the sensor  124  should still have noise components similar to those sensed by the sensor  104  but should not have components intentionally related to motion of a rodent. 
         [0020]    The two sensors  104 ,  124  are shown separately in  FIG. 1  to indicate that they are two separate sensors. However, they could both be attached to the cage  102  as long as the sensor  124  is not directly sensing motion of a rodent. For example, one common rodent cage is, in fact, four distinct cages arranged on a single base  108 . Each such cage would have its own separate sensor  104  but a single isolation pad  106  may still be utilized. In such a setup, three of the four cages could be occupied (and thus each have a respective sensor  104 ) while one cage could be unoccupied (and, thus, have a sensor  124 ). This location would ensure the sensor  124  is exposed to similar noise-causing phenomena as the rodent sensors  104 . 
         [0021]    One of ordinary skill will recognize that there are a variety of different ways to locate the sensor  124  near the other sensors  104  without departing from the scope of the present invention. Each cage could have a sensor  104  and sensor  124  or each four-cage unit could have one sensor  124  and four sensors  104 . However, fewer of the sensors  124  can be used as well. For example, a table that supports tens or dozens of the four-cage units could have one sensor  124  to generate a noise signal that can be used in relation to all of those cages on that table which each have a separate sensor  104  sensing rodent motion. In a lab in which there are multiple tables, each table could have its own sensor  124  or a single sensor  124 , preferably located centrally in the room, could be used for the entire room. 
         [0022]    In the example environment of  FIG. 1 , the following specific example is provided to aid with understanding underlying principles of the present disclosure. These specific details are but one example of how signals related to the motion of rodents can be accurately obtained. 
         [0023]    The PVDF sensor  104 ,  124  can be sized such that it has a slightly large footprint than the floor of the cage  102 . One example PVDF sensor can be 17.78 cm by 17.78 cm square and have a dielectric with a thickness of about 110 μm. The sensor  104  can be covered by a protective sheet (not shown) and bedding for the animal (not shown) can be placed on the protective sheet. 
         [0024]    In an example environment in which the cage  102  is actually multiple cages such that there are a number of sensors near one another, the isolation pad  106  can be used to reduce cross-talk between the different sensors. The pad  106  can, for example, be about 1.6 mm thick, constructed from Shore A 70 Durometer silicon, and extend substantially over the entire top of the base  108  underneath one or more sensors  104 . 
         [0025]    An example capacitance of the PVDF sensor sheet  104  is approximately 30 nF and when coupled to an input differential amplifier, followed by a low-pass filter, effectively band-pass filters the pressure signals with 3 dB down points at 1.35 Hz and 20 Hz. The differential amplifier provides a high pass effect and can, for example, have a linear gain of about 22. The amplified signals can be fed to a multi-channel data acquisition board (e.g., National Instruments PCI  6224 ), sampled at 128 samples per second, and quantized with 16 bits. 
         [0026]      FIG. 2A  depicts a block level diagram of acquiring sensor signals in accordance with the principles of the present invention. A sensor  230  (which can be either the sensor  104  or  124  of  FIG. 1 ) generates electrical, analog signals that are communicated to an amplifier  232 . These amplified signals can then be digitized. For example, an analog-to-digital converter  234  can be used to quantize the analog signal into a sampled digital signal  236 . One of ordinary skill will recognize that the amplification level (i.e., gain) of the amplifier  232  and the sampling rate of the A-to-D converter  234  can vary without departing from the scope of the present invention. 
         [0027]      FIG. 2B  depicts a flowchart of an exemplary method for performing noise cancellation in accordance with the principles of the present invention. The data acquisition and collection system  114  can implement a noise cancellation algorithm in accordance with the principles of the present invention. The algorithm can be executable instruction stored on a computer or processor that, when executed, perform the steps depicted in  FIG. 2B  and  FIG. 3 . 
         [0028]    The signal r(t)=s(t)+n(t) in  FIG. 2B  is sensed and amplified, in step  200 , and includes a component s(t) related to rodent movement and some component n(t) related to unwanted noise. This signal, r(t), as mentioned above can be digitized into signal r[k]=s[k]+n[k]. Separately, using a nearby sensor, ñ(t) is sensed. in step  202 , and represents a noise refrence signal that provides some insight into the characteristics of n(t). This signal is also digitized to produce signal ñ[k]. Next, in step  204 , a noise cancellation algorithm is implemented to produce a signal {circumflex over (r)}[k−d]. This signal has a delay d, which can be zero, such that a current sample (i.e. [k−d]) of {circumflex over (r)}[k−d] relies, in part on, “future” noise reference samples ñ[k]. 
         [0029]    Although an example noise cancellation technique is described herein with respect to  FIG. 3 , one of ordinary skill will recognize that, generally, the noise cancellation step  204  combines the signals ñ[k] and r[k] in such a way as to reduce the effect n[k] has on the signal {circumflex over (r)}[k−d]. This final signal is what is analyzed in step  206  to classify the current behavior of a rodent. By compensating for the noise that may be present in the environment, improvements can be made to a sensor&#39;s accuracy for detecting animal behaviors tied to low level signals such as those that result from sleeping, resting, REM sleep, NREM sleep, breath rates, etc. One of ordinary skill in this field will recognize that signal signatures are known that indicate a rodent is awake and breathing normal, is REM sleeping or is non-REM sleeping. The quantized, sampled, and delayed signal with reduced noise {circumflex over (r)}[k−d] can now be analyzed to classify these types of behavior events of a rodent within a cage. 
         [0030]      FIG. 3  depicts details of an exemplary noise cancellation algorithm in accordance with the principles of the present invention. Similar to the steps discussed earlier with respect to  FIG. 2B , the digitized signals ñ[k] and {circumflex over (r)}[k−d] are generated from sensor signals in steps  302  and  304 , respectively. In steps  306 ,  308  each of the signals can be filtered in a similar manner. For example, a band-pass filter could range from about 1 to 20 Hz or from about 0.5 Hz to 25 Hz. In one particular beneficial use related to sleep/awake monitoring, a filter associated with the amplifier circuitry can low pass filter from about 18 Hz and, then, the data acquisition and collection software/hardware can band pass filter from between 0.5 Hz to about 8 Hz. 
         [0031]    The filtered noise reference signal is passed to an adaptive filter in step  314 . In step  312 , a determination is made if the reference noise signal is of sufficient power to be considered a noise signal that can be used for noise cancellation. If the reference noise signal is not useful, then a switch  316  can be set to block any noise cancellation signal generated by the adaptive filter. If the reference noise signal is useful then the switch  316  is set to pass the output of the adaptive filter to the combiner at step  318 . 
         [0032]    Returning now to the right-hand side of  FIG. 3 , the filtered, digitized rodent sensor signal is delayed, in step  312 , by a number of samples, d, before being combined with the noise cancellation signals from the adaptive filter. For example, with a LMS filter, the filter can have a filter of order  32  and a delay of 16 samples (that is at a 128 Hz sampling rate) that corresponds to a delay of about 0.128 seconds. Usually orders between 30 and 60 work well with delays ranging from 0.1 to 0.5 seconds. Thus, the delayed rodent sensor signal is combined in step  318  with the output of the adaptive filer (depending on the state of the switch  316 ) to produce a noise-cancelled signal {circumflex over (r)}[k−d]  324 . This signal  324  includes a component that is related to movement or motion of a rodent in a cage and may still also include a noise component. However, the noise component in this latter signal  324  is far less than the original noise component n(t) due to the noise cancellation steps. 
         [0033]    As shown in  FIG. 3 , the adaptive filter is fed both the reference noise signal and the output signal  324  in order to produce the values used to cancel noise in the rodent sensor signal r(t) (or, r[k]). One particular class of adaptive filters that is beneficial for step  314  is known as least mean squares filters. 
         [0034]    Least mean squares (LMS) algorithms are a class of adaptive filter used to mimic a desired filter by finding the filter coefficients that produce a desired outcome. The basic idea behind LMS filter is to approach the optimum filter weights by updating the filter weights in a manner to converge to the optimum filter weight. In particular, as shown in  FIG. 3 . the filter can be adaptive to minimize the output power with a model of the noise. Assuming the noise and signal are for the most part independent (orthogonal), an optimal fitting of a noise signal to the data will minimize power and leave the signal intact. In other words the filter coefficients are adjustable to minimize output power. 
         [0035]    Accordingly, the algorithm of  FIG. 3  includes step  320  which determines if the quantized, sampled, and delayed signal with reduced noise {circumflex over (r)}[k−d] has an output power that is over a predetermined threshold value. If so, then a determination is made that the system may be unstable and the adaptive filter coefficients are reset. 
         [0036]    The previous description is provided to enable any person skilled in the art to practice the various embodiments described herein. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments. Thus, the claims are not intended to be limited to the embodiments shown herein, but are to be accorded the full scope consistent with each claim&#39;s language, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” All structural and functional equivalents to the elements of the various embodiments described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. No claim element is to be construed under the provisions of 35 U.S.C. §112, sixth paragraph, unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited using the phrase “step for.”