Systems and methods are described for implementing a catheter model to estimate shape of a deformable catheter in a three-dimensional space. The catheter model includes two or more model segments that correspond to two or more segments of the deformable catheter. Each model segment includes a length and location of model electrode(s) and/or model magnetic sensor(s) corresponding electrodes and/or magnetic sensors of the deformable catheter. Variable shape parameter define a curvature of the segment. Varying the shape parameters generates a plurality of potential catheter shapes. In conjunction with generating the potential catheter shapes, impedance and/or magnetic responses (e.g., measured responses) are obtained for the physical electrodes and/or physical magnetic sensors of the deformable catheter. Using a selected one (e.g., most likely) of the potential catheter shapes and the measured responses, the shape parameters are updated and a catheter shape is generated and displayed.

A switch module for an electronic device detects translational inputs and defines at least portion of a conductive path from an input surface of the electronic device to a processing unit of the electronic device. The switch module may be a component of a crown assembly for detecting rotational inputs, translational inputs, touch inputs and/or biological signals such as electrocardiogram (ECG) signals. The switch module may include a conductive dome and a friction guard that is positioned between the conductive dome and the actuation member of the crown assembly. The conductive dome and/or the friction guard may define at least a portion of the conductive path from the input surface to the processing unit.

A medical device capable of determining its location is provided. The medical device comprises a memory, one or more antennas, one or more processors coupled with the memory and the one or more antennas, a location manager component executable by the one or more processors. The location manager component is configured to receive first location information from a first location information source and second location information from a second location information source, to rank the first location information source and the second location information source according to a hierarchy of location information sources, the hierarchy of location information sources specifying that the first location information source is of higher rank than the second location information source, determine an approximate location of the medical device based on the first location information, and improve the accuracy of the approximate location based on the second location information.

A medical device capable of determining its location is provided. The medical device comprises a memory, one or more antennas, one or more processors coupled with the memory and the one or more antennas, a location manager component executable by the one or more processors. The location manager component is configured to receive first location information from a first location information source and second location information from a second location information source, to rank the first location information source and the second location information source according to a hierarchy of location information sources, the hierarchy of location information sources specifying that the first location information source is of higher rank than the second location information source, determine an approximate location of the medical device based on the first location information, and improve the accuracy of the approximate location based on the second location information.

The present invention provides a carotid blood pressure detection device, comprising: a first sensing unit, a second sensing unit, and a controller connected or coupled to the first sensing unit and the second sensing unit. The first sensing unit is disposed on a subject's neck and adjacent to a first position of the subject's carotid arteries. The second sensing unit is disposed on the subject's neck and adjacent to a second position of the subject's carotid arteries. The controller derives a mean arterial pressure of a section of the subject's carotid arteries that lies between the first position and the second position of the subject's carotid arteries from pulse wave data measured and obtained by the first sensing unit and pulse wave data measured and obtained by the second sensing unit.

The EKG cord management system is a cable management system. The EKG cord management system is configured for use with the leads of an EKG machine. The EKG cord management system comprises a plurality of lead structures, a probe connector, and a housing. The EKG cord management system deploys the plurality of lead structures from the housing. The EKG cord management system retracts the plurality of lead structures into the housing. Each lead structure selected from the plurality of lead structures measures electrical activity in a human body. The probe connector electrically connects each of the plurality of lead structures to a machine known as an EKG machine.

A driving assistance system and a driving assistance method are provided. The driving assistance system includes a physiological information sensing system, an external physical symptom detection system, and a processing device. The physiological information sensing system is configured to sense physiological information of a driver. The external physical symptom detection system is configured to detect an external physical symptom of the driver. The processing device is coupled to the physiological information sensing system and the external physical symptom detection system. When the physiological information of the driver and the external physical symptom of the driver are abnormal, the processing device initiates an emergency procedure.

A driving assistance system and a driving assistance method are provided. The driving assistance system includes a physiological information sensing system, an external physical symptom detection system, and a processing device. The physiological information sensing system is configured to sense physiological information of a driver. The external physical symptom detection system is configured to detect an external physical symptom of the driver. The processing device is coupled to the physiological information sensing system and the external physical symptom detection system. When the physiological information of the driver and the external physical symptom of the driver are abnormal, the processing device initiates an emergency procedure.

A wearable stethoscope includes a sound sensing device for collecting heart sound signals of the body, an electrocardiogram sensing device for collecting electrocardiogram signals of the body, a processing unit, powered by a power source, coupled to the sound sensing device and the electrocardiogram sensing device to perform data preprocessing on the above-mentioned signals to remove background noise. An external electronic computing device is set up to analyze and process the fed pre-processed ECG signal and heart sound signal, perform feature extraction in combination with the user's physiological parameters and medical records to obtain related feature vectors, input the feature vectors into a screening model, obtain an evaluation value and give corresponding suggestions. After screening, users can upload the verification results to the cloud database to expand the existing training samples for further optimizing the parameters of the screening model.

A wearable stethoscope includes a sound sensing device for collecting heart sound signals of the body, an electrocardiogram sensing device for collecting electrocardiogram signals of the body, a processing unit, powered by a power source, coupled to the sound sensing device and the electrocardiogram sensing device to perform data preprocessing on the above-mentioned signals to remove background noise. An external electronic computing device is set up to analyze and process the fed pre-processed ECG signal and heart sound signal, perform feature extraction in combination with the user's physiological parameters and medical records to obtain related feature vectors, input the feature vectors into a screening model, obtain an evaluation value and give corresponding suggestions. After screening, users can upload the verification results to the cloud database to expand the existing training samples for further optimizing the parameters of the screening model.