Researchers Submit Patent Application, “Microelectromechanical Accelerometer Based Sensor System”, for Approval (USPTO 20190292044)

2019 OCT 16 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Washington, D.C., NewsRx journalists report that a patent application by the inventors Carroll, William Joseph (Vernon, CT); Molinsky, Bradley Dean (Bloomfield, CT); Dunst, Michael J. (Unionville, CT); Tipton, Thomas Andrew (Milton, GA); Battaglini, Joseph S. (Newington, CT), filed on June 11, 2019, was made available online on September 26, 2019.

The patent’s assignee is Hartford Fire Insurance Company (Hartford, Connecticut, United States).

News editors obtained the following quote from the background information supplied by the inventors: “The use of portable electronic devices has grown exponentially recently, and in particular, the use of monitoring devices in sporting, health and work areas to measure activity levels, as well measuring environmental or user parameters such as temperature, heart rate, altitude, etc. has increased substantially. Sometimes, data related to user activities may be acquired from multiple devices, such as a smart phone, a GPS (Global Positioning System) device, a pedometer, a heart rate monitor, etc.

“Microelectromechanical systems (MEMS) technology such as accelerometers for measuring acceleration and gyroscopes for measuring angular velocity have been implemented within several related devices and applications. For example, individual accelerometer and gyroscope based sensors are currently being used in mobile phones, gaming consoles, digital cameras, etc.

“MEMS devices generally are capable of producing one or more analog output signals that correspond to a given measurement and, therefore, an analog-to-digital converter (ADC) is usually required to convert the analog output signals into corresponding digital signals for digital signal processing. Applications that include a MEMS device and an ADC, typically implement multi-chip board level technology to couple the MEMS device to the ADC, and/or implement the MEMS device and the ADC on separate chips, printed circuit boards (PCBs), or modules.

“These devices enable the capture and collection of data that may be used in a variety of applications. It would be desirable to utilize these devices and information in more efficient and impactful applications.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “The present invention in some embodiments relates to a micro-electro-mechanical-system (MEMS) based sensor system for detecting and analyzing activity levels comprising a wireless router having a transceiver operable to communicate with at least one server programmed to operate as a world wide web server and having a network data adapter to communicate with one or more third party networks; and a wearable microelectromechanical sensor configured to connect to a mobile electronic device, the microelectromechanical sensor including a wireless communication transceiver provided internal to the microelectromechanical sensor wherein the microelectromechanical sensor wirelessly communicates with the mobile electronic device; the mobile electronic device configured to wirelessly receive and display user activity data collected by the microelectromechanical sensor, the mobile electronic device having a transceiver for transmitting the received user activity data to a remote server system device via a communications network, the remote server system configured to analyze the user activity data to determine an associated activity classification associated with the user activity data, each activity classification corresponding to a predetermined condition and an associated condition benefit, the mobile electronic device enabled to transmit instructions to microelectromechanical sensor in order to vary a sampling condition of the microelectromechanical sensor in response to the determined activity classification.

“In other embodiments, the present invention relates to a microelectromechanical sensor based system for measuring activity levels comprising at least one wearable microelectromechanical sensor configured within a mobile electronic device, the microelectromechanical sensor including a wireless communication transceiver provided internal to the microelectromechanical sensor for transmitting the measured user activity data to a remote server system device via a communications network, the remote server system configured to analyze the user activity data to determine an associated activity classification associated with the user activity data, each activity classification corresponding to a predetermined condition and an associated condition benefit, wherein the determined activity classification determines a content of one or more electronic communications transmitted by the remote server system to a user device.

“In further embodiments, the present invention related to a microelectromechanical sensor based system comprising an accelerometer based sensor configured to connect to a mobile electronic device, the accelerometer based sensor including a wireless communication transceiver provided internal to the accelerometer sensor wherein the accelerometer based sensor wirelessly communicates with the mobile electronic device; the mobile electronic device configured to wirelessly receive user activity data collected by the accelerometer based sensor, the mobile electronic device having a transceiver for transmitting the received user activity data to a remote server system device via a communications network, the received user activity data triggering a pricing parameter adjustment associated with the user, the remote server system configured to analyze the user activity data to determine an associated activity classification associated with the user activity data, the mobile electronic device enabled to transmit instructions to the accelerometer based sensor in order to validate the determined activity classification.”

The claims supplied by the inventors are:

“1. A non-tangible, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a Micro-Electro-Mechanical-System (“MEMS”) based method for detecting and analyzing activity levels, the method comprising: collecting, by a wearable MEMS sensor, user activity data of a user wearing the MEMS sensor; wirelessly transmitting, from a transceiver of the wearable MEMS sensor to a mobile electronic device, the collected user activity data, wherein the mobile electronic device is adapted to display the user activity data; forwarding, from the mobile electronic device to a data adapter of a remote server system device via a wireless router, the collected user activity data; analyzing, by the remote server system device, the user activity data to determine an associated activity classification, each activity classification corresponding to a pre-determined condition and an associated condition benefit; and automatically generating, by a computer processor of the remote server system device, an exception condition for an investigator upon detection of a potential fraudulent condition based on a comparison of the sensed user activity data with a historical profile of that particular user’s past activities and a predictive model.

“2. The medium of claim 1, wherein the wearable MEMS sensor includes a nonvolatile memory having stored representations of instructions to electronically correlate the user activity data with a reference scale of activity levels.

“3. The medium of claim 1, wherein the mobile electronic device includes an accelerometer and a memory having stored instructions, and a processor circuit.

“4. The medium of claim 1, wherein the wearable MEMS sensor comprises at least a plurality of accelerometers capturing representations of actual user activity that are indicative of a potential fraudulent condition related to at least one of a short term disability or a long term disability.

“5. The medium of claim 1, wherein the MEMS sensor generates an output signal indicative of an activity level that corresponds to a certain user condition.

“6. The medium of claim 5, wherein location data is used to infer an activity level.

“7. The medium of claim 6, wherein the remote server system device outputs an electronic communication to the user in the event the user condition does not correspond to the detected activity level.

“8. The medium of claim 1, where the mobile electronic device electronically correlates the user activity levels with a predetermined classification of allowable activity levels, the user being provided a differential discount.

“9. The medium of claim 1, wherein the mobile electronic device includes a processor circuit and a volatile memory and the processor circuit is operable to store into the volatile memory a time-window of data responsive to activity of the user, wherein the activity may qualify the user for a benefit.

“10. The medium of claim 9, wherein the benefit is a pricing adjustment.

“11. The medium of claim 1, wherein the MEMS sensor includes a processor and a memory, wherein and the processor is configured to generate an activity classification of the user activity.

“12. The medium of claim 1, wherein the activity classification qualifies the user for a pricing adjustment.

“13. The medium of claim 1, wherein the predictive model is associated with at least one of: (i) a neural network, (ii) a Bayesian network, (iii) a hidden Markov model, (iv) an expert system, (v) a decision tree, (vi) a collection of decision trees, and (vii) a support vector machine.

“14. A non-tangible, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a Micro-Electro-Mechanical-System (“MEMS”) based method for detecting and analyzing activity levels, the method comprising: measuring, by at least one wearable MEMS sensor configured within a mobile electronic device, user activity data, the MEM sensor including a wireless communication transceiver internal to the MEMS sensor for transmitting the user activity data; receiving, by a remote server system device via a communications network, the user activity data; analyzing, by the remote server system device, the user activity data to determine an associated activity classification associated with the user activity data, each activity classification corresponding to a predetermined condition and an associated condition benefit; automatically generating, by the remote server system device, an exception condition for an investigator upon detection of a potential fraudulent condition based on a comparison of the sensed user activity data with a historical profile of that particular user’s past activities and a predictive model; and determining, based on the determined activity classification, a content of one or more electronic communications transmitted by the remote server system device to a user device.

“15. The medium of claim 14, wherein the electronic communication is configured for display on the mobile electronic device.

“16. The medium of claim 15, wherein the determined activity classification is based on historical analysis of activity levels associated with a variety of conditions.

“17. The medium of claim 16, wherein the conditions relate to a sedentary or an active condition that are correlated with a compliant and a non-compliant classification.

“18. The medium of claim 14, wherein the wearable MEMS sensor includes a nonvolatile memory having stored representations of instructions to electronically correlate the user activity data with a reference scale of activity levels.

“19. The medium of claim 14, wherein the mobile electronic device includes an accelerometer and a memory having stored instructions, and a processor circuit.

“20. The medium of claim 14, wherein the wearable MEMS sensor comprises at least a plurality of accelerometers capturing representations of actual user activity that are indicative of a potential fraudulent condition related to at least one of a short term disability or a long term disability.

“21. The medium of claim 14, wherein the MEMS sensor generates an output signal indicative of an activity level that corresponds to a certain user condition.

“22. The medium of claim 21, wherein location data is used to infer an activity level.”

For additional information on this patent application, see: Carroll, William Joseph; Molinsky, Bradley Dean; Dunst, Michael J.; Tipton, Thomas Andrew; Battaglini, Joseph S. Microelectromechanical Accelerometer Based Sensor System. Filed June 11, 2019 and posted September 26, 2019. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220190292044%22.PGNR.&OS=DN/20190292044&RS=DN/20190292044

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