Energy harvesting for sensor systems

Patent metadata

Field	Value
Publication number	US-11266329-B2
Application number	US-201716084729-A
Country	US
Kind code	B2
Filing date	Mar 14, 2017
Priority date	Mar 14, 2016
Publication date	Mar 8, 2022
Grant date	Mar 8, 2022

Abstract

Described is an energy harvesting system comprising a transducer that generates an electric signal from ambient energy, and a processor adapted to process the electric signal to determine and output a characteristic of a source of the ambient energy. The characteristic may be a spoken word classification.

First claim

The invention claimed is:

1. An energy harvesting system comprising:
a transducer that generates an electric signal from ambient energy;
a power conditioning circuit to rectify and regulate the electric signal to produce a regulated electric signal;
an energy storage to store the regulated electric signal and provide power to the processor and a transmitter; and
a processor adapted to process the electric signal to determine a characteristic of a source of the ambient energy that is associated with a user's gait and is indicative of a user's identification by:
obtaining gait cycle vectors from the electric signal;
estimating a set of coefficients vectors by optimizing the gait cycle vectors using a predetermined dictionary;
generating a sparse fusion model by combining the set of coefficients vectors;
determining a minimal residual using the sparse fusion model and a projection matrix; and
determining the characteristic using the minimum residual, and to output the characteristic.

2. The system of claim 1 wherein the gait cycle vectors are obtained by segmenting the electrical signal by gait cycles to provide a plurality of gait cycle vectors.

3. The system of claim 2 wherein combining the estimated coefficients vectors to reduce noise comprises generating a weighted sum of the estimated coefficients vectors.

4. The system of claim 3 wherein the weight for a given estimated coefficients vector is found by normalizing a sparsity concentration index calculated for that estimated coefficients vector.

5. The system of claim 2 wherein the projection matrix is an optimal projection matrix produced using a heuristic algorithm.

6. The system of claim 1 wherein optimizing the gait cycle vectors comprises using 1 1 optimization and the predetermined dictionary.

7. A method for determining a characteristic of a source of ambient energy that is associated with a user's gait and is indicative of a user's identification, the method comprising:
receiving and transforming ambient energy into an electrical signal;
rectifying and regulating the electric signal by a power conditioning circuit to produce a regulated electric signal;
storing the regulated electric signal in an energy storage to provide power to the processor and a transmitter;
obtaining gait cycle vectors from the electric signal;
estimating a set of coefficients vectors by optimizing the gait cycle vectors using a predetermined dictionary;
generating a sparse fusion model by combining the set of coefficients vectors;
determining a minimal residual using the sparse fusion model and a projection matrix;
determining the characteristic using the minimum residual, and outputting the characteristic.

8. The method of claim 7 wherein the gait cycle vectors are obtained by segmenting the electrical signal by gait cycles to provide a plurality of gait cycle vectors.

9. The method of claim 8 wherein combining the estimated coefficients vectors to reduce noise comprises generating a weighted sum of the estimated coefficients vectors.

10. The method of claim 9 wherein the weight for a given estimated coefficients vector is found by normalizing a sparsity concentration index calculated for that estimated coefficients vector.

11. The method of claim 7 wherein the projection matrix is an optimal projection matrix produced using a heuristic algorithm.

12. The method of claim 7 wherein optimizing the gait cycle vectors comprises using 1 1 optimization and the predetermined dictionary.

Assignees

• Nat Ict Australia Ltd

Inventors

• Hassan Mahbub
• Hu Wen
• Khalifa Sara
• Seneviratne Aruna

Classifications

• H02N2/186

  Vibration harvesters · CPC title

• H02N2/181

  Circuits; Control arrangements or methods · CPC title

• H02N2/18

  producing electrical output from mechanical input, e.g. generators (for measurement devices G01) · CPC title

• A61B2560/0242

  adapted to measure environmental factors, e.g. temperature, pollution · CPC title

• A61B5/117 Primary

  Identification of persons (methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00) · CPC title