System and method for screening orthostatic hypotension by using heart rate-based machine learning algorithm, and wearable measurement device
AssigneeTobedtx
InventorsByung Jo Kim, Jung Bin Kim
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Abstract
An orthostatic hypotension screening system using a heart rate-based machine learning algorithm includes an input unit configured to receive a variable comprising at least one of a patient's age, blood pressure, an expiration (E)-inspiration (I) difference and an E:I ratio calculated from a heart rate, and a Valsalva ratio calculated according to a Valsalva method; and a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the variable received through the input unit.
Claims8
An orthostatic hypotension screening system using a heart rate-based machine learning algorithm comprising:
- an input unit configured to receive a variable comprising at least one of a patient's age, blood pressure, an expiration (E)-inspiration (I) difference and an E:I ratio calculated from a heart rate, and a Valsalva ratio calculated according to a Valsalva method;
- and
- a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the variable received through the input unit.
An orthostatic hypotension screening system using a heart rate-based machine learning algorithm comprising:
- a wearable measuring device worn on a patient's body and configured to measure the patient's heart rate;
- a processing device configured to calculate an expiration (E)-inspiration (I) difference and an E:I ratio from the heart rate measured by the wearable measuring device, and calculate a Valsalva ratio from the heart rate measured by the wearable measuring device according to a Valsalva method;
- and
- a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the E-I difference, the E:I ratio, and the Valsalva ratio calculated by the processing device.
An orthostatic hypotension screening method using a heart rate-based machine learning algorithm comprising:
- calculating an expiration (E)-inspiration (I) difference and an E:I ratio from a patient's heart rate;
- calculating a Valsalva ratio according to a Valsalva method;
- and
- determining whether the patient has orthostatic hypotension according to a machine learning algorithm based on the E-I difference, the E:I ratio, and the Valsalva ratio.
Dependencies are inferred from the claim text.