Nec corporation (20240120042). LEARNING DEVICE, DETERMINATION DEVICE, METHOD FOR GENERATING TRAINED MODEL, AND RECORDING MEDIUM simplified abstract

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LEARNING DEVICE, DETERMINATION DEVICE, METHOD FOR GENERATING TRAINED MODEL, AND RECORDING MEDIUM

Organization Name

nec corporation

Inventor(s)

Yuji Ohno of Tokyo (JP)

LEARNING DEVICE, DETERMINATION DEVICE, METHOD FOR GENERATING TRAINED MODEL, AND RECORDING MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240120042 titled 'LEARNING DEVICE, DETERMINATION DEVICE, METHOD FOR GENERATING TRAINED MODEL, AND RECORDING MEDIUM

Simplified Explanation

The patent application describes a learning device that acquires biometric information and medical chart information of a patient to determine if the patient is in agitation.

  • Acquisition unit for acquiring biometric information and medical chart information of a patient
  • Selection unit for selecting biometric information that allows determination of patient agitation
  • Model generation unit for generating an agitation determination model using selected biometric information

Potential Applications

This technology could be applied in healthcare settings, such as hospitals or nursing homes, to monitor and assess patient agitation levels.

Problems Solved

This technology helps healthcare providers quickly and accurately determine if a patient is in agitation, allowing for timely intervention and appropriate care.

Benefits

- Improved patient care through early detection of agitation - Enhanced efficiency in healthcare settings - Reduction in potential risks associated with patient agitation

Potential Commercial Applications

"Enhancing Patient Care: The Role of Biometric Technology in Agitation Detection"

Possible Prior Art

There may be prior art related to biometric monitoring devices in healthcare settings, but specific examples are not provided in the abstract.

Unanswered Questions

How does the device differentiate between different levels of agitation in patients?

The abstract does not specify how the device distinguishes between varying degrees of agitation in patients.

What types of biometric information are most effective in determining patient agitation?

The abstract does not detail which specific biometric indicators are most useful in accurately determining patient agitation levels.


Original Abstract Submitted

this learning device comprises: an acquisition unit for acquiring biometric information of a patient and medical chart information of the patient; a selection unit for selecting, on the basis of the medical chart information, the biometric information of the patient that allows the determination of whether the patient is in agitation; and a model generation unit for generating an agitation determination model for determining whether a subject patient is in agitation, by using the selected biometric information and on the basis of the biometric information of the subject patient.