Provided are systems and method for obtaining electric signal biosignal readings using a portable device.

The present teachings relate to monitoring the condition of a subject with a contactless system for sensing biopotential signals comprising: a support surface; one or more inner layers; a plurality of contactless electrode units within the one or more inner layers; one or more outer layers; and wherein the plurality of contactless electrode units are arranged in an inner shape within an outer shape such that the contactless electrode units form the vertices of the inner shape and the outer shape. The method includes the steps of: providing a support surface having one or more sensing devices embedded therein; positioning the subject at least partially on the support surface; acquiring data from an electrocardiograph reading on the subject for a predetermined amount of time; outputting the data of the step (c); and analyzing the data of the step (c), by identifying one or more biomarkers consistent with a disease condition.

The present teachings relate to monitoring the condition of a subject with a contactless system for sensing biopotential signals comprising: a support surface; one or more inner layers; a plurality of contactless electrode units within the one or more inner layers; one or more outer layers; and wherein the plurality of contactless electrode units are arranged in an inner shape within an outer shape such that the contactless electrode units form the vertices of the inner shape and the outer shape. The method includes the steps of: providing a support surface having one or more sensing devices embedded therein; positioning the subject at least partially on the support surface; acquiring data from an electrocardiograph reading on the subject for a predetermined amount of time; outputting the data of the step (c); and analyzing the data of the step (c), by identifying one or more biomarkers consistent with a disease condition.

Automatically determining a medical recommendation for a patient based on multiple medical images from multiple different medical imaging modalities. In some embodiments, a method may include receiving a first and second medical images of a patient from first and second medical imaging modalities, mapping a first region of interest (ROI) on the first medical image to a second ROI on the second medical image, generating first annotation data related to the first ROI and second annotation data related to the second ROI, generating first medical clinical data related to the first ROI and second medical clinical data related to the second ROI, inputting, into a machine learning classifier, the first and second annotation data and the first and second medical clinical data, and automatically determining, by the machine learning classifier, a medical recommendation for the patient related to a medical condition of the patient.

A massage apparatus includes: a first bio-signal measurement unit which is formed in an arm massage unit and includes at least one electrode positioned at a portion where the palm of a user is placed, and which is movable back and forth on the basis of the position of the hand of the user; a second bio-signal measurement unit which is formed in a foot massage unit and includes at least one electrode positioned at the rear portion of the ankle of the user, and is movable back and forth; and a control unit for acquiring information on the physical condition of the user on the basis of bio-signals obtained from the first bio-signal measurement unit and the second bio-signal measurement unit.

A massage apparatus includes: a first bio-signal measurement unit which is formed in an arm massage unit and includes at least one electrode positioned at a portion where the palm of a user is placed, and which is movable back and forth on the basis of the position of the hand of the user; a second bio-signal measurement unit which is formed in a foot massage unit and includes at least one electrode positioned at the rear portion of the ankle of the user, and is movable back and forth; and a control unit for acquiring information on the physical condition of the user on the basis of bio-signals obtained from the first bio-signal measurement unit and the second bio-signal measurement unit.

Automatically determining a medical recommendation for a patient based on multiple medical images from multiple different medical imaging modalities. In some embodiments, a method may include receiving a first and second medical images of a patient from first and second medical imaging modalities, mapping a first region of interest (ROI) on the first medical image to a second ROI on the second medical image, generating first annotation data related to the first ROI and second annotation data related to the second ROI, generating first medical clinical data related to the first ROI and second medical clinical data related to the second ROI, inputting, into a machine learning classifier, the first and second annotation data and the first and second medical clinical data, and automatically determining, by the machine learning classifier, a medical recommendation for the patient related to a medical condition of the patient.

In a bioelectrode capable of detecting biometric information of a living body in touch with the bioelectrode, the bioelectrode includes a base, a first conductive layer that is laminated on a surface side of the base, that is formed by dispersing scale-shaped conductive particles in an insulating binder, and that has extensibility, and a second conductive layer that is laminated on a surface side of the first conductive layer, that has conductivity, and that is harder than the first conductive layer. The second conductive layer is disposed to be exposed at the surface side of the base where the second conductive layer is touchable with the living body. An amount of conductive particles filled in the second conductive layer is smaller than an amount of the conductive particles filled in the first conductive layer. The second conductive layer has a larger outer contour than the first conductive layer.

In a bioelectrode capable of detecting biometric information of a living body in touch with the bioelectrode, the bioelectrode includes a base, a first conductive layer that is laminated on a surface side of the base, that is formed by dispersing scale-shaped conductive particles in an insulating binder, and that has extensibility, and a second conductive layer that is laminated on a surface side of the first conductive layer, that has conductivity, and that is harder than the first conductive layer. The second conductive layer is disposed to be exposed at the surface side of the base where the second conductive layer is touchable with the living body. An amount of conductive particles filled in the second conductive layer is smaller than an amount of the conductive particles filled in the first conductive layer. The second conductive layer has a larger outer contour than the first conductive layer.

Automatically determining a medical recommendation for a patient based on multiple medical images from multiple different medical imaging modalities. In some embodiments, a method may include receiving a first and second medical images of a patient from first and second medical imaging modalities, mapping a first region of interest (ROI) on the first medical image to a second ROI on the second medical image, generating first annotation data related to the first ROI and second annotation data related to the second ROI, generating first medical clinical data related to the first ROI and second medical clinical data related to the second ROI, inputting, into a machine learning classifier, the first and second annotation data and the first and second medical clinical data, and automatically determining, by the machine learning classifier, a medical recommendation for the patient related to a medical condition of the patient.