US11382510B2 - Biological data tracking system and method - Google Patents
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- US11382510B2 US11382510B2 US16/274,701 US201916274701A US11382510B2 US 11382510 B2 US11382510 B2 US 11382510B2 US 201916274701 A US201916274701 A US 201916274701A US 11382510 B2 US11382510 B2 US 11382510B2
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Definitions
- This disclosure relates to the field of monitoring systems utilizing data from sensors applied to living beings. More particularly, the disclosure pertains to a system for configuring and collecting data directly from a set of wearable sensors using an application that is downloadable and executable via a web browser.
- a number of physiological data sensors have been developed to assist athletes during training or competition. Some of these sensors are wearable or fixed to the athlete's skin to measure various metrics and wirelessly send the measurements to a cell phone or tablet for display. Typically, each sensor is associated with an application program which a user must download and install on the cell phone or tablet. Each application receives and displays data from a single sensor. Some of the application programs may be capable of uploading data to a server for later processing.
- a biological data tracking system includes at least one biological data sensor, a computer, and an application program.
- the at least one sensor may include at least two different types of sensors which may communicate with the application using different communication interfaces.
- the computer includes an internet connection and browser software.
- the application which executes within the browser, is programmed to establish wireless communications with each of the sensors, receive streams of data from the sensors, and display, via the browser software, readings derived from streamed data.
- the application may also transmit commands to the sensors to change sensor settings. At least one of the readings may be derived from data streams from two different sensors.
- the system may also include a server configured to receive the streams of data via an internet connection and compute the readings.
- the server may also transmit the application program to the browser in response to a user accessing a web page.
- a biological data tracking system includes an application and a server.
- the application establishes wireless communications with each of a plurality of wearable data sensors, receives streams of data from the sensors, and displays, via browser software, readings derived from streamed data.
- the server may transmit the application to the browser in response to a user accessing a web page.
- the application may transmit the streams of data to the server which then calculates the readings.
- the plurality of wearable sensors may include at least two different types of sensors, including sensors that communicate with the application using different communication interfaces. At least one of the readings may be derived based on data streams from two different sensors.
- the application may also transmit commands to a subset of the plurality of sensors to change sensor settings.
- a method of tracking biological data includes transmitting an application from a server to a browser, detecting at least one wearable sensor, wirelessly receiving a data stream from the sensor, and displaying a reading.
- the server transmits the application to the browser in response to a user accessing a web page.
- the application detects the sensors and directly receives the data streams.
- the readings are derived from at least one of the data streams and displayed in the browser.
- the method may also include transmitting the data streams from the browser to the server and transmitting the reading from the server to the browser.
- the application may send a command to the sensor to change a sensor setting.
- the sensors may include at least two types of sensors which may transmit data streams to the application using two different communication interfaces.
- FIG. 1 is a schematic diagram of a biological data tracking system.
- FIG. 2 is a block diagram illustrating the state of a computer system before a user launches the data tracking system webpage.
- FIG. 3 is a flowchart for using the biological data tracking system of FIG. 1 .
- FIG. 4 is a block diagram illustrating the state of the system after an intermediate step in the method of FIG. 3 .
- FIG. 5 is an exemplary display page for selecting sensors.
- FIG. 6 is an exemplary data entry screen for assigning sensors to subjects and for setting sensor parameters.
- FIG. 7 is a block diagram illustrating the state of the system during an operation phase.
- FIG. 8 is an exemplary data entry screen for selecting readings for display.
- FIG. 9 is an exemplary display page for readings.
- FIG. 1 illustrates a system to simultaneously track and analyze biological data from multiple subjects.
- the subjects may be, for example, athletes during training or competition. Alternatively, the subjects could be, for example, pets, livestock, or humans other than athletes. Two such subjects, 10 and 12 , are shown in FIG. 1 .
- the actual number of subjects may vary from one to several dozen or even more.
- Each subject is monitored by at least one wireless wearable sensor 14 , 16 , and 18 .
- Wearable sensors include sensors that are attached directly to the subject's skin, sensors that are embedded under the subject's skin, and sensors that are attached to the subject's clothing. Various types of sensors detect various types of data.
- Some biological sensors may measure physiological metrics such as, for example, electro-cardiogram signals, blood flow, body temperature, perspiration levels, or breathing rate. Some biological sensors may detect biomechanical metrics such as, for example, position or accelerations in various directions from which a subject's movements may be characterized. In addition to biological data about the individual subject, some sensors may measure environmental conditions such as ambient temperature and humidity.
- the sensors communicate with the other parts of the system wirelessly, for example using Bluetooth Low Energy (BLE) technology.
- BLE Bluetooth Low Energy
- the sensors communicate with a personal computer 20 via a Bluetooth dongle 22 and an antenna 24 .
- the antenna 24 may be a directional antenna positioned to provide high gain with respect to the area in which the subjects move and low gain with respect to other areas.
- a carefully selected and positioned directional antenna provides multiple advantages over a non-directional antenna. First, the higher gain in the areas occupied by the subjects increases the transmission range. Secondly, especially in spectator sports, there may be a high number of signals in the same frequency range from surrounding areas that could cause interference.
- personal computer 20 is connected to a server 26 by some combination of Wifi and hardwired internet connections.
- FIG. 2 illustrates the status of the system at the beginning of a data monitoring session.
- Personal computer 20 includes an operating system 30 that coordinates interactions between various types of hardware and software.
- Personal computer 20 may be, for example, a laptop computer or a desktop computer.
- the hardware present includes Bluetooth hardware such as the dongle 22 and antenna 24 illustrated in FIG. 1 .
- the personal computer also has an internet connection 34 which may include both hardware and software aspects.
- FIG. 3 is a flow chart for a typical operational sequence of utilizing the system of FIG. 1 .
- the subjects put on the sensors and switch them on if necessary.
- FIG. 4 illustrates the status of the system following step 40 . Note that no connection yet exists between the sensors and the personal computer.
- a user 44 ( FIG. 4 ), interacting with the user interface hardware 32 , opens a web browser 46 .
- a web browser is a general-purpose software application that is commonly found on personal computers.
- a user may start the web browser by, for example, clicking on an icon with a pointing device such as a mouse.
- the web browser starts by displaying a default page such as a search engine.
- the user opens web page 48 which is associated with the tracking system of FIG. 1 .
- the user may open this page by typing in a Uniform Resource Locator (URL), by using a search engine, or by selecting a saved entry from a previous session.
- URL Uniform Resource Locator
- FIG. 4 illustrates the state of the system following step 50 .
- a web page is a software entity that conveys information, usually from a server, to the user and collects information and commands from the user to be conveyed to the server.
- An application on the other hand, performs non-trivial computation and may be programmed to interact with hardware besides the user interface hardware 32 and the internet connection 34 .
- Internet Application 52 is a Software as a Service (SaaS) application, meaning that, from the user's perspective, the functionality is being provided as a service on the internet. The user does not direct, and doesn't need to be aware of, any downloading or installation of software to his or her computer.
- SaaS Software as a Service
- the Application 52 utilizes the Bluetooth hardware 22 and 24 to detect the presence of sensors 14 , 16 , and 18 and instructs web page 48 to display a list of available sensors to the user.
- the user selects the sensors of interest, for example, by clicking on buttons displayed by web page 48 .
- FIG. 5 illustrates an exemplary webpage 48 for selecting sensors and setting sensor parameters. Sensors that have already been selected are displayed in a first area of the screen 70 . For each such sensor, the display indicates the type of sensor, the quantities which the sensor is capable of measuring, and two buttons. Button 72 permits the user to configure the sensor as discussed below. Button 74 permits the user to un-select the sensor.
- Sensors that have been detected but not yet selected are displayed in a second area of the screen 76 .
- the display indicates the type of sensor, the quantities which the sensor is capable of measuring, and one button.
- Button 78 permits the user to select the sensor, after which it is moved to area 70 .
- the application connects to the selected sensors.
- the user assigns particular sensors to particular subjects.
- the system may provide a default value to simplify this process when only one subject is involved.
- the application sends commands to the sensors to set sensor parameters and start streaming measurements.
- the parameters may include items like mode of operation, sampling rate, data range, gain, etc.
- the user may be presented with the ability to edit parameter settings through a data entry screen such as that illustrated in FIG. 6 .
- Text entry box 80 permits the user to assign the sensor to a particular subject.
- Selection boxes in area 82 allow the user to set sensor parameters. The state of the system after selecting sensors and assigning them to subjects is illustrated in FIG. 7 .
- the user selects which readings should be displayed for each subject. This may be performed via a data entry screen such as that illustrated in FIG. 8 . A checkbox is displayed for each measurement that is available. Note that the number of measurements available may exceed the number of selected sensors, as some sensors are capable of measuring multiple quantities. Also, some readings may be derived from multiple data streams. Such readings are called aggregated insights. Some aggregated insights may be derived from data streams from different types of sensors. For example, the fatigue reading 84 may be derived from a combination of heart rate (from an electro-cardiogram sensor), blood pressure, ambient temperature, etc.
- a first athlete's reaction time may be derived by comparing an acceleration measurement from the first athlete to an acceleration measurement from a second athlete.
- the ability to gather these different data streams in a single application greatly facilitates computation of these aggregated insights. If the data streams are collected by separate applications and then transmitted to the server, the latency of transmission may preclude real-time or near real-time display. Near real-time means low enough latency for the subject to react to the reading during the activity. Additionally, variability of latency between sensors may lead to the data streams not being properly synchronized as they arrive at the server.
- the system operates in a continuous fashion with the application receiving data streams from the sensors at 60 , the application sending those data streams to the server at 62 , the server processing the data streams to calculate readings of interest at 64 , and the server sending the readings to a web page for display at 66 .
- a data stream may involve electro-cardiogram measurements every millisecond and the server may process this stream to calculate a heart rate reading every second.
- FIG. 9 illustrates an exemplary webpage for displaying readings.
- Communication interfaces include command sets, data formats, and message exchange sequences. For example, one type of sensor might begin sending measurements once every 20 milliseconds in response to a single command to begin streaming data. Another type of sensor might require that the measurement frequency be specified in the “begin streaming” command. Yet another type of sensor might send individual measurements in response to request commands such that the system must send requests commands at the desired frequency.
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Claims (25)
Priority Applications (11)
Application Number | Priority Date | Filing Date | Title |
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US16/274,701 US11382510B2 (en) | 2019-02-13 | 2019-02-13 | Biological data tracking system and method |
KR1020217028737A KR20210139252A (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
AU2020223038A AU2020223038A1 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
US17/054,277 US20210225505A1 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
EP20756424.6A EP3923804A4 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
CN202080014423.2A CN113710152A (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
PCT/US2020/018063 WO2020168045A1 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
JP2021547072A JP7542861B2 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
SG11202108786XA SG11202108786XA (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
CA3130205A CA3130205A1 (en) | 2019-02-13 | 2020-02-13 | Biological data tracking system and method |
US17/860,231 US20220338736A1 (en) | 2019-02-13 | 2022-07-08 | Biological data tracking system and method |
Applications Claiming Priority (1)
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US16/274,701 US11382510B2 (en) | 2019-02-13 | 2019-02-13 | Biological data tracking system and method |
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US11882237B1 (en) | 2022-11-30 | 2024-01-23 | Gmeci, Llc | Apparatus and methods for monitoring human trustworthiness |
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US12186050B2 (en) * | 2021-07-16 | 2025-01-07 | AnneAlise Bonistalli | Biometric monitoring systems and methods |
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CA3130205A1 (en) | 2020-08-20 |
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JP7542861B2 (en) | 2024-09-02 |
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US20220338736A1 (en) | 2022-10-27 |
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