Method and system for detecting an event and determine information about it (like its strength) using resistive state changes of a memristor

Patent metadata

Field	Value
Publication number	US-11622731-B2
Application number	US-201716342072-A
Country	US
Kind code	B2
Filing date	Oct 16, 2017
Priority date	Oct 18, 2016
Publication date	Apr 11, 2023
Grant date	Apr 11, 2023

Abstract

The present invention provides a method and system for processing data from an event, such as a neurological event. When a neurological event occurs, a spike in a neural waveform is generated. The spike can be detected and used to determine information about the neurological event. The method uses data values from a resistive switching component capable of undergoing a resistive state change when a voltage is applied to it. The data values represent a sequence of resistive state changes of the resistive switching component which correspond to the neurological event. The method further comprises processing the received data values to identify a resistive state change corresponding to the neurological event and to obtain information about the neurological event. Thus, a method and system for processing neural spikes is provided.

First claim

The invention claimed is:

1. A method for processing a signal from at least one sensor configured to convert a physical phenomenon to an output signal that can be measured to detect an event, comprising:
applying the output signal to a resistive switching component, optionally wherein the output signal is transformed prior to applying the output signal to the resistive switching component;
receiving data values representing a sequence of resistive state changes of the resistive switching component resulting from applying the output signal to the resistive switching component, wherein the resistive switching component is capable of undergoing a non-volatile resistive state change when a voltage above a threshold voltage is applied across the resistive switching component, wherein the resistive switching component is configured to change its resistive state as a function of the integral of the voltage; and
processing the received data values to identify a resistive state change corresponding to the event, thereby detecting the event, and to obtain information about the event other than temporal information from the resistive state change; and
wherein the data values have a non-linear relationship with a resistance of the resistive switching component.

2. The method of claim 1 , wherein the identifying of a resistive state change corresponding to an event comprises identifying a feature in the received data values, the feature comprising a time window of data values in which a change in the data values between any two data points in a predetermined time interval is greater than a predefined value, wherein the feature indicates a resistive state change, which is when the change in resistance is a large enough change within a fixed time period.

3. The method of claim 2 , wherein the processing comprises obtaining information about the event from a size of the change in the data values of the feature.

4. The method of claim 2 , wherein the processing comprises obtaining information about an event from both 1) a size of the change in the data values of the feature; and 2) a size of a reference data value within the feature, wherein the reference data value comprises one of the following: a data value corresponding to a start of the resistive state change of the feature; a data value corresponding to an end of the resistive state change of the feature; a data value corresponding to a predetermined percentile value of the feature or to an average value of the feature.

5. The method of claim 4 , wherein the processing further comprises determining which of a plurality of classes the event belongs to.

6. The method of claim 5 , wherein classifying is carried out exclusively on data values for which the reference data value is below a threshold.

7. The method of claim 1 , wherein the processing further comprises obtaining temporal information of the event.

8. The method of claim 1 , wherein the data values are obtained by sampling a resistance of the resistive switching component at equal intervals.

9. The method of claim 1 , wherein the data values are proportional to a derivative of the resistance with respect to time.

10. The method of claim 1 , wherein the output is transformed prior to applying the output to the resistive switching component.

11. The method of claim 1 , wherein the event is a neurological event.

12. The method of claim 1 , wherein the resistive switching component is configured to change its resistive state as a function of a weighted integral of the voltage.

13. A system for processing a signal from at least one sensor configured to convert a physical phenomenon to an output voltage signal that can be measured to detect an event, the system comprising:
a resistive switching component configured to receive the output signal from the at least one sensor and to undergo a non-volatile resistive state change when a voltage above a threshold voltage is applied across the resistive switching component, optionally wherein the output signal is transformed prior to applying the output signal to the resistive switching component, and wherein the resistive switching component is configured to change its resistive state as a function of an integral of the voltage; and
a processor configured to:
receive data values representing a sequence of resistive state changes of the resistive switching component resulting from applying the output from the at least one sensor to the resistive switching component; and
process the received data to identify a resistive state change corresponding to the event, thereby detecting the event, and to obtain information about the event other than temporal information from the resistive state change; and
wherein the data values have a non-linear relationship with a resistance of the resistive switching component.

14. The system of claim 13 , wherein the event is a neurological event.

15. The system of claim 13 , wherein the at least one sensor is further configured to measure the event and to output a voltage relating to the event.

16. The system of claim 15 , wherein the event is a neurological event and the at least one sensor is a neurological sensor.

17. The system of claim 13 , wherein the resistive switching component is configured to change its resistive state as a function of a weighted integral of the voltage.

18. A method for processing data from at least one sensor configured to measure an event, comprising:
applying an output relating to the event from the at least one sensor to a resistive switching component, optionally wherein the output is transformed prior to applying the output to the resistive switching component,
receiving data values representing a sequence of resistive state changes of a resistive switching component resulting from applying the output from the at least one sensor to the resistive switching component, wherein the resistive switching component is capable of undergoing a non-volatile resistive state change when a voltage above a threshold voltage is applied across the resistive switching component, wherein the resistive switching component is configured to change its resistive state as a function of an integral of the voltage; and
processing the received data values to identify a resistive state change corresponding to the event and to obtain information about the event other than temporal information from the resistive state change,
wherein the identifying of a resistive state change corresponding to an event comprises identifying a feature in the received data values, the feature comprising a time window of data values in which a change in the data values between any two data points in a predetermined time interval is greater than a predefined value, wherein the feature indicates a resistive state change, which is when the change in resistance is a large enough change within a fixed time period,
wherein the processing comprises obtaining information about an event from both 1) a size of the change in the data values of the feature; and 2) a size of a reference data value within the feature, wherein the reference data value comprises one of the following: a data value corresponding to a start of the resistive state change of the feature; a data value corresponding to an end of the resistive state change of the feature; a data value corresponding to a predetermined percentile value of the feature or to an average value of the feature,
wherein the processing further comprises determining which of a plurality of classes the event belongs to, and
wherein classifying is carried out exclusively on

Assignees

• Univ Southampton

Inventors

• Gupta Isha
• Serb Alexantrou
• Prodromakis Themistoklis

Classifications

• A61B5/304

  Switching circuits · CPC title

• G11C13/0007

  comprising metal oxide memory material, e.g. perovskites · CPC title

• A61B5/7282 Primary

  Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818) · CPC title

• A61B2562/0285

  Nanoscale sensors · CPC title

• G06N3/049

  Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs · CPC title