System and method for determining the posture of a person
First Claim
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1. A system for determining a posture of a person, comprising:
- at least one motion sensor configured to be affixed to the person, the at least one motion sensor configured to measure k measurement axes, k being greater than or equal to two;
at least one filter coupled to the at least one motion sensor and configured to generate output signals that include first signals with frequencies higher than a first threshold selected for each axis of measurement, and second signals with frequencies below a second threshold lower than or equal to said first threshold;
a calculation module configured to calculate a density of probability of a first variable representing said first signals, said first variable modeled by a Chi-2 law with a degree of freedom equal to k, and to calculate a density of probability of a second variable representing said second signals, said second variable being a one-dimensional variable representative of the second signals along the k axes of measurement and being modeled by a Gaussian law; and
an analysis module configured to determine a posture of the person out of a plurality of postures by combining;
joint densities of probabilities of said first and second variables, the joint densities of probabilities being defined for each posture of the plurality of postures; and
probabilities of transition between two successive postures of the plurality of postures.
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Abstract
A system for determining the posture of a person has a motion sensor (CM) with at least one axis of measurement, which is provided with fixing means (MF) for rigidly connecting said motion sensor (CM) to a user. Analysis means (AN) are also included for determining a posture of the user. The analysis means (AN) utilize: (A) joint densities of probabilities of a low-frequency component and a high-frequency component, these densities of probabilities being defined for each posture; and (B) probabilities of transition between two successive postures.
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Citations
12 Claims
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1. A system for determining a posture of a person, comprising:
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at least one motion sensor configured to be affixed to the person, the at least one motion sensor configured to measure k measurement axes, k being greater than or equal to two; at least one filter coupled to the at least one motion sensor and configured to generate output signals that include first signals with frequencies higher than a first threshold selected for each axis of measurement, and second signals with frequencies below a second threshold lower than or equal to said first threshold; a calculation module configured to calculate a density of probability of a first variable representing said first signals, said first variable modeled by a Chi-2 law with a degree of freedom equal to k, and to calculate a density of probability of a second variable representing said second signals, said second variable being a one-dimensional variable representative of the second signals along the k axes of measurement and being modeled by a Gaussian law; and an analysis module configured to determine a posture of the person out of a plurality of postures by combining; joint densities of probabilities of said first and second variables, the joint densities of probabilities being defined for each posture of the plurality of postures; and probabilities of transition between two successive postures of the plurality of postures. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for determining a posture of a person, comprising:
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processing output signals of at least one motion sensor to produce first signals with frequencies above a first threshold selected for each axis of measurement, and second signals with frequencies below a second threshold lower than or equal to said first threshold, wherein the at least one motion sensor is configured to measure k measurement axes, k being equal to or greater than two; calculating a density of probability of a first variable representative of said first signals and a density of probability of a second variable representative of said second signals, said first variable being modeled by a Chi-2 law with a degree of freedom equal to k, and said second variable being a one-dimensional variable representative of the second signals along the k axes of measurement and being modeled by a Gaussian law; and determining a posture of the person as a function of time, by using a hidden Markov model with N states corresponding respectively to N postures, the determination being carried out by utilizing; joint densities of probabilities of said second and first variables, the joint densities of probabilities being defined for each posture of the N postures, and probabilities of transition between two successive postures of the N postures.
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Specification