Abstract:
A method for associating a plurality of patient monitoring sensors with an appropriate patient is disclosed herein. The method includes estimating a sensor location for each of a plurality of sensors that are operatively connected to a patient, transmitting the sensor location estimate from each of the sensors to a wireless device such that the sensor location estimate does not pass through an on-patient hub before reaching the wireless device, and implementing the sensor location estimate to assign each of the sensors that are disposed within a predefined region to a single patient.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    Patients within a hospital environment are generally monitored by system having a plurality of different sensors. The sensors may, for example, include a wristband sensor adapted to provide identity and location data, a pulse oximetry sensor, an electrocardiogram (ECG) sensor, and/or an electroencephalogram (EEG) sensor. Conventional patient monitoring systems also include an on-patient hub device adapted to receive data from the sensors, and to transmit such data to a hospital network. In order to manage data transfer in conventional patient monitoring systems, the specific type of data being transferred to the on-patient hub at any given time must be precisely identified and correlated with its appropriate sensor. It is therefore generally necessary to apply each sensor in a specific order and thereafter to remove each sensor in a specific order. One problem with such conventional patient monitoring systems is that the process of managing the transfer of data from the sensors to the on-patient hub device is complex and labor intensive. Another problem with such conventional patient monitoring systems is that the on-patient hub adds weight and cost to the system. 
       BRIEF DESCRIPTION OF THE INVENTION 
       [0002]    The above-mentioned shortcomings, disadvantages and problems are addressed herein which will be understood by reading and understanding the following specification. 
         [0003]    In an embodiment, a method for associating a plurality of patient monitoring sensors with an appropriate patient includes estimating a sensor location for each of a plurality of sensors that are operatively connected to a patient, transmitting the sensor location estimate from each of the sensors to a wireless device such that the sensor location estimate does not pass through an on-patient hub before reaching the wireless device, and implementing the sensor location estimate to assign each of the sensors that are disposed within a predefined region to a single patient. 
         [0004]    In another embodiment, a method for associating a plurality of patient monitoring system sensors with an appropriate patient includes acquiring sensor motion data for each of a plurality of sensors that are operatively connected to a patient, transmitting the sensor motion data from each of the sensors to a wireless device such that the sensor motion data does not pass through an on-patient hub before reaching the wireless device, implementing the sensor motion data to identify one or more common patterns of motion, and assigning each of the sensors having a common pattern of motion to a single patient. 
         [0005]    In another embodiment, a method for associating a plurality of patient monitoring system sensors with an appropriate patient includes acquiring pulse data with each of a plurality of sensors that are operatively connected to a patient, transmitting the pulse data from each of the sensors to a wireless device such that the pulse data does not pass through an on-patient hub before reaching the wireless device, identifying each of the sensors that acquired pulse data having a common pulse data characteristic, and assigning each of the identified sensors to a single patient. 
         [0006]    Various other features, objects, and advantages of the invention will be made apparent to those skilled in the art from the accompanying drawings and detailed description thereof. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0007]      FIG. 1  is a schematic diagram illustrating a patient monitoring system connected to a patient; 
           [0008]      FIG. 2  is a method for implementing the patient monitoring system of  FIG. 1  in accordance with an embodiment; 
           [0009]      FIG. 3  is a method for implementing the patient monitoring system of  FIG. 1  in accordance with another embodiment; and 
           [0010]      FIG. 4  is a method for implementing the patient monitoring system of  FIG. 1  in accordance with yet another embodiment. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0011]    In the following detailed description, reference is made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific embodiments that may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the embodiments, and it is to be understood that other embodiments may be utilized and that logical, mechanical, electrical and other changes may be made without departing from the scope of the embodiments. The following detailed description is, therefore, not to be taken as limiting the scope of the invention. 
         [0012]    Referring to  FIG. 1 , a schematically illustrated patient monitoring system  10  is connected to a patient  12  in accordance with an exemplary embodiment. The patient monitoring system  10  includes one or more sensors  14  and an algorithm  16 . 
         [0013]    According to one embodiment, the sensors  14  each comprise a Wi-Fi wireless device compliant with the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard such that sensor data is wirelessly transmittable. The sensors  14  may include devices adapted to monitor patient location, pulse rate (e.g., a pulse oximetry sensor), cardiac electrical activity (e.g., an electrocardiogram or ECG sensor), electrical activity in a patient&#39;s brain (e.g., an electroencephalogram or EEG sensor), blood pressure, respiration, etc. 
         [0014]    The sensors  14  may be referred to as “equal sensors” because there is no hierarchical relationship among the sensors  14  and none of the sensors  14  incorporate an on-patient hub. Advantageously, the absence of a hierarchical relationship enables the sensors to be implemented individually or in any combination with out regard to the order in which they are attached to or removed from a patient. Obviating the need for an on-patient hub reduces the overall expense and weight of the patient monitoring system  10 . 
         [0015]    The algorithm  16  may be stored on the hospital network  18 . The algorithm  16  may, for example, be configured to perform one or more of the following operations: assign the sensors  14  to an appropriate patient; collect any sensor data from the sensors  14 ; and compile the sensor data into a patient record  19 . For purposes of this disclosure, the assignment of sensors to an appropriate patient refers to the process of correlating or associating the individual sensors (and any data therefrom) with the patient to which the sensors are physically and/or operatively connected. A plurality of patient records  19  each containing data that pertains to a different patient may be stored on the hospital network  18 . 
         [0016]    It should be appreciated that a typical hospital environment may include multiple patient monitoring systems  10  that are each configured to monitor a different patients. It therefore becomes necessary to correlate the data from each of a plurality of different sensors with the patient to which the sensors are attached. Accordingly, a plurality of different methods for assigning the sensors  14  to an appropriate patient (i.e., the patient to which the sensors are attached) and for implementing the patient monitoring system  10  will hereinafter be described in detail. 
         [0017]      FIG. 2  is flow chart illustrating a method  20  in accordance with an embodiment. The method  20  can be included as a feature of the algorithm  16 . The individual blocks of the flow chart shown in  FIG. 2  represent steps that may be performed in accordance with the method  20 . 
         [0018]    Referring to  FIGS. 1 and 2 , at step  22  the method  20  estimates the location of each of the sensors  14 . This step can be performed, for example, by incorporating a known locating device or system into each of the sensors  14 . 
         [0019]    At step  24 , acquired location data is transmitted from each of the sensors  14 . Step  24  can be performed in accordance with either of two distinct embodiments. According to a first embodiment, the sensors  14  are configured to transmit any acquired location data to the algorithm  16 . Therefore, step  24  may be performed in accordance with the first embodiment by transmitting location data from each of the sensors  14  to the algorithm  16  such that the algorithm  16  can assign the sensors  14  to an appropriate patient. According to a second embodiment, each of the sensors  14  are configured to both transmit and receive any acquired location data. Therefore, step  24  may be performed in accordance with the second embodiment by transmitting location data among the sensors  14  so that the sensors  14  can assign themselves to an appropriate patient. 
         [0020]    At step  26 , the location data acquired by the sensors  14  is implemented to assign all the sensors  14  within a predefined region to a single patient. According to one embodiment, the predefined region may include all sensors located in sufficiently close proximity to each other. The requisite degree of proximity is selectable but may, for example, include any sensors located within four feet of each other so that a first sensor attached to a typical patient&#39;s head and a second sensor attached to the patient&#39;s leg would both be assigned to the same individual. If there is any ambiguity as to which patient a given sensor should be assigned at step  26 , that sensor may be flagged and later manually assigned. In this manner, the likelihood of assigning sensor data to the wrong patient is minimized. 
         [0021]    At step  28 , sensor data collected from any of the sensors  14  that have been assigned is compiled in a convenient form such as, for example, the patient record  19 . Patient records  19  for each of a plurality of different patients can then be stored on the hospital network  18 . 
         [0022]      FIG. 3  is flow chart illustrating a method  30  in accordance with an embodiment. The method  30  can be included as a feature of the algorithm  16 . The individual blocks of the flow chart shown in  FIG. 3  represent steps that may be performed in accordance with the method  30 . 
         [0023]    Referring to  FIGS. 1 and 3 , at step  32  the method  30  monitors the motion of each of the sensors  14 . This step can be performed, for example, by incorporating a known motion tracking device or system into each of the sensors  14 . 
         [0024]    At step  34 , acquired motion data is transmitted from each of the sensors  14 . Step  34  can be performed in accordance with either of two distinct embodiments. According to a first embodiment, the sensors  14  are configured to transmit any acquired motion data to the algorithm  16 . Therefore, step  34  may be performed in accordance with the first embodiment by transmitting motion data from each of the sensors  14  to the algorithm  16  such that the algorithm  16  can assign the sensors  14  to an appropriate patient. According to a second embodiment, each of the sensors  14  are configured to both transmit and receive any acquired motion data. Therefore, step  34  may be performed in accordance with the second embodiment by transmitting motion data among the sensors  14  so that the sensors  14  can assign themselves to an appropriate patient. 
         [0025]    At step  36 , the motion data acquired by the sensors  14  is implemented to identify common patterns of motion and to assign all the sensors  14  having a common pattern of motion to a single patient. This step is predicated on the assumption that sensors attached to a single individual will share common motion traits. For example, there will be many instances when the sensors and the patient are all in motion, and further instances when the sensors and the patient are all at rest. Evaluating this sensor motion data may therefore be useful in the assignment of the sensors  14  to the appropriate patient. This sensor motion data may be used in combination with the previously described sensor location data in order to assign the sensors  14 . If there is any ambiguity as to which patient a given sensor should be assigned at step  36 , that sensor may be flagged and later manually assigned. In this manner, the likelihood of assigning sensor data to the wrong patient is minimized. 
         [0026]    At step  38 , sensor data collected from any of the sensors  14  that have been assigned is compiled in a convenient form such as, for example, the patient record  19 . Patient records  19  for each of a plurality of different patients can then be stored on the hospital network  18 . 
         [0027]      FIG. 4  is flow chart illustrating a method  40  in accordance with an embodiment. The method  40  can be included as a feature of the algorithm  16 . The individual blocks of the flow chart shown in  FIG. 4  represent steps that may be performed in accordance with the method  40 . 
         [0028]    Referring to  FIGS. 1 and 4 , at step  42  the method  40  acquires pulse data from each of the sensors. Many types of sensors such as pulse oximeter sensors and ECG sensors are adapted to acquire pulse data as their primary function. Additionally, it has been observed that EEG sensors attached to a patient&#39;s head can also be implemented to monitor a patient&#39;s pulse, and that conventional EEG sensors generally include a pulse signal component. This pulse signal component has typically been viewed as noise but may be useful for purposes of step  42 . Other sensors that are not adapted to monitor pulse as a primary function and that do not provide a pulse signal component may require the addition of a separate pulse monitoring device. 
         [0029]    At step  44 , acquired pulse data is transmitted from each of the sensors  14 . Step  44  can be performed in accordance with either of two distinct embodiments. According to a first embodiment, the sensors  14  are configured to transmit any acquired pulse data to the algorithm  16 . Therefore, step  44  may be performed in accordance with the first embodiment by transmitting pulse data from each of the sensors  14  to the algorithm  16  such that the algorithm  16  can assign the sensors  14  to an appropriate patient. According to a second embodiment, each of the sensors  14  are configured to both transmit and receive any acquired pulse data. Therefore, step  44  may be performed in accordance with the second embodiment by transmitting pulse data among the sensors  14  so that the sensors  14  can assign themselves to an appropriate patient. 
         [0030]    At step  46 , the pulse data acquired by the sensors  14  is implemented to identify each of the sensors  14  having similar pulse data characteristics, and to assign all the sensors  14  identified as having similar pulse data characteristics to a single patient. This step is predicated on the assumption that multiple patients are unlikely to share pulse characteristics such as pulse rate, pulse phase, and pulse variation. Evaluating this pulse data may therefore be useful in the assignment of the sensors  14  to the appropriate patient. This pulse data may be used in combination with the previously described sensor pulse data and/or the previously described sensor location data in order to assign the sensors  14 . If there is any ambiguity as to which patient a given sensor should be assigned at step  46 , that sensor may be flagged and later manually assigned. In this manner, the likelihood of assigning sensor data to the wrong patient is minimized. 
         [0031]    At step  48 , sensor data collected from any of the sensors  14  that have been assigned is compiled in a convenient form such as, for example, the patient record  19 . Patient records  19  for each of a plurality of different patients can then be stored on the hospital network  18 . 
         [0032]    While the invention has been described with reference to preferred embodiments, those skilled in the art will appreciate that certain substitutions, alterations and omissions may be made to the embodiments without departing from the spirit of the invention. Accordingly, the foregoing description is meant to be exemplary only, and should not limit the scope of the invention as set forth in the following claims.