Apparatus and methods are described including identifying that a subject suffers from sleep apnea. Positive airway pressure (PAP) is applied to the subject via a mask placed on a face of the subject. A respiratory-related parameter of the subject is sensed, while the mask is on the face of the subject, and a need of the subject for respiratory support is assessed, responsively to the respiratory-related parameter. In accordance with the assessed need, the mask is configured to regulate the PAP provided to the subject's face. Other applications are also described.

The present invention relates to the field of diagnostics. Specifically, it relates to a method for assessing Huntington's disease of the pre-manifest stage in a subject comprising the steps of determining at least one performance parameter from a dataset of fine motoric measurements from said subject, comparing the determined at least one performance parameter to a reference, and assessing Huntington's disease of the pre-manifest stage in the subject based on said comparison. Yet, the invention contemplates a device and a system for carrying out the aforementioned methods and the use of such device or system for assessing Huntington's disease of the pre-manifest stage in the subject.

Embodiments of the disclosure are drawn to implantable stimulator with machine learning based classifier. An implantable system includes sensors which provide sensor information to an implantable unit. The implantable unit uses a classifier on the sensor information to select a stimulation procedure which is applied via a stimulation electrode. The classifier may be generated by a trained machine learning model. The classifier may be trained on an external unit which is not implanted in the subject. The classifier may be trained based on sensor information from the implanted sensors as well as symptom information.

A method and a related device to determine the kinetic state of a subject includes the steps of determining a signal indicative of the acceleration trend on the three Cartesian axes; processing the signal to limit the frequency band and preferably reduce artifacts and compensate the offset of the output signals from a multi-axial measurement system; analyzing frequency and spectrum through the transformation of the signal with the Fournier transform; computing the power spectral density for each Cartesian axis; and comparing the spectral density with a characteristic pattern of a movement.

A security platform architecture is described herein. A user identity platform architecture which uses a multitude of biometric analytics to create an identity token unique to an individual human. This token is derived on biometric factors like human behaviors, motion analytics, human physical characteristics like facial patterns, voice recognition prints, usage of device patterns, user location actions and other human behaviors which can derive a token or be used as a dynamic password identifying the unique individual with high calculated confidence. Because of the dynamic nature and the many different factors, this method is extremely difficult to spoof or hack by malicious actors or malware software.

In one embodiment, a method for detecting tremors includes generating electromagnetic fields proximate to an individual's body part with a circuit to generate an eddy current density on a surface of the body part, receiving magnetic fields generated by the eddy current with the circuit that change a resonant frequency of the circuit, sensing the resonant frequency as it changes over time, and determining a movement frequency of the body part from the resonant frequency to quantify tremors in the body part.

The disclosure provides a theseometer or proprioceptometer for objectively quantifying the proprioceptive performance of a subject such as a human. The disclosed theseometer is a device comprising a clear, rigid material or screen having or exhibiting a distinguishable target embraced by a series of concentric rings, a digital camera with a lens concentric to the target, a base unit comprising an electronic processor and memory for analyzing data and, optionally, a wheeled base to provide mobility and portability.

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.

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

A system and method are disclosed including receiving, from a sensor, motion data captured from a human, the motion data representative of involuntary human motions. In one embodiment, the method includes storing, in a memory, the motion data captured from the human. In one embodiment, the method includes processing the motion data captured by the human to determine a cycle bandwidth of the involuntary human motions across the motion data. In one embodiment, the method includes outputting the cycle bandwidth of the involuntary human motions across the motion data.