According to an embodiment of the disclosure, an electronic device may include a communication module, a display, a photoplethysmography (PPG) sensor, a motion sensor, a memory, and at least one processor. The at least one processor may be configured to obtain a first light signal and a second light signal sensed by the PPG sensor and three-axis acceleration signals sensed by the motion sensor, identify a tremorous state using the first light signal, the second light signal, and the three-axis acceleration signals, and display information indicating the tremorous state on the display. Other embodiments may also be possible.

A peripheral nerve stimulator can be used to stimulate a peripheral nerve to treat essential tremor, Parkinsonian tremor, and other forms of tremor. The stimulator can have electrodes that are placed circumferentially around the patient's wrist or arm. Specific nerves in the wrist or arm can be targeted by appropriate spacing of the electrodes. Positioning the electrodes on generally opposing sides of the target nerve can result in improved stimulation of the nerve. The stimulation pattern may alternate between the nerves. Improved stimulation algorithms can incorporate tremor feedback, external data, predictive adaptation, and long-term monitoring data.

The disclosed system receives various physiological as well as physical information concerning a patient, and operational data from a ventilation device and medication delivery device, and provides the physiological and physical information, together with the operational data, to a neural network configured to analyze the information and data. The system receives, from the neural network, an assessment classification of the patient corresponding to at least one of a pain assessment, a sepsis assessment, and a delirium assessment of the patient based on providing to the neural network the determined physiological state of the patient, the determined physical state of the patient, the determined operational mode of the ventilator, the medication delivery information, and the received diagnostic information for the patient, and adjusts, based on the assessment classification, a ventilation parameter that influences the operational mode of a ventilator providing ventilation to the patient.

Embodiments herein disclose computer-implemented methods, computer program products and computer systems for performing neurological diagnostic assessments. The computer-implemented method may include processors configured for receiving biometric activity data corresponding to user extremity movement from a mobile device associated with a user. Further, the computer-implemented method may include processors configured for transmitting the biometric activity data to a machine learning model. Furthermore, the computer-implemented may be configured for processing, using the machine learning model, the biometric activity data to generate first model output data corresponding to a first score. Even further, the computer-implemented method may include processors configured for determining that the first model output data corresponds to a neurological disorder classification based at least on the first score exceeding a predetermined threshold.

The present invention comprises a novel kit with a wearable unit along with associated intelligent entities and non-intrusive tremor relieving interventions. The interventions include an automatically controllable TENS intervention unit with associated cables and electrodes and a buzzer. The wearable unit along with associated intelligent entities detects involuntary movement signals (tremors) in the limbs by measuring the acceleration in multiple dimensions, and ingeniously analyzes the accelerations to identify and isolate occurrences of tremors. This information is analyzed and monitored over time to provide significant insight about the tremors such as the dominant frequency (or frequencies), percent time with tremor, median tremor duration, and intensity. The TENS unit provides electrical stimulation which can dampen the intensity of involuntary movement and/or temporarily suspend tremor activity. This (TENS) unit can be manually or automatically controlled. The automatic control mode controls the TENS unit depending on the onset of tremors, tremor duration, and intensity of tremors. Furthermore, the parameters of this automatic control can be adjusted.

This invention controls stimulation levels and cycling cadence on an FES ergometer to minimize or prevent the occurrence of spasm in spinal cord injured or other neurologically impaired patients.

A tremor-reduction system is provided that delivers electric current to a body region of a subject that is associated with a tremor. A computing device stores received data associated with a tremulous movement of the body region and determines measurements associated with the stored data. If a magnitude of the most recent tremulous movement is the same as or greater than magnitudes associated with prior tremulous movements, characteristics of a subsequent electric current to be applied to the body region may be adjusted.

A user interface device is adapted to provide tremor cancellation. The user interface device comprises a user interface for determining a position from a physical user input and a position output for providing a time-ordered output stream of position data, but also provides a tremor learning module and a tremor cancellation module. The tremor learning module can be trained to identify tremor patterns for a user by comparing time-ordered output streams of position data produced by the user with predetermined representations. The tremor cancellation module is adapted to apply the tremor patterns learned for the user to cancel tremors in a time-ordered stream of position data produced by the user to create an output stream of position data which is corrected for user tremor. A method of training and then using such a user interface device is also described.

A system for detecting an anomalous event in a person includes a body in contact with a skin surface of a person; a heat source for heating the skin surface to a target temperature; a skin temperature sensor for measuring a temperature of the skin surface in contact with the heat source; a blood volume sensor for measuring a blood volume of the skin surface; and a hardware processor communicatively coupled to the heat source, the blood volume sensor, the skin temperature sensor, and an environmental temperature sensor. The hardware processor is configured to receive a baseline blood volume signal, output a heating signal to the heat source to initiate a heating cycle, receive a second blood volume signal from the blood volume sensor, compare the second blood volume signal to the baseline blood volume signal, and determine whether an anomalous biologic event has occurred.

In accordance with one embodiment, a method for determining changes in health of a user is disclosed. The method includes sensing multi-dimensional motion of a body part of a user to generate a first multi-dimensional motion signal at a first time and date; in response to the first multi-dimensional motion signal, generating a first neuro-mechanical fingerprint; generating a first health measure in response to the first NFP and user calibration parameters; sensing multi-dimensional motion of the body part of the user to generate another multi-dimensional motion signal at another time and date; in response to the another multi-dimensional motion signal, generating another neuro-mechanical fingerprint; generating another health measure in response to the another NFP and the user calibration parameters; and comparing the first health measure with the another health measure to determine a difference representing the health degradation of the user.