The embodiments of the present disclosure disclose a system and method. The system may include at least one storage device configured to storage computer instruction; and at least one processor, in communication with the storage device. When executing the computer instructions, the at least one processor is configured to direct the system to perform operations including: obtaining a sensing signal of at least one sensing device; identifying a signal feature of the sensing signal; and determining, based on the signal feature, an operation of a target object associated with the at least one sensing device.

A method of characterising tremor stability in a subject is described for a subject having an involuntary tremor symptomatic of a neurological disorder. The method comprising: identifying a series of tremor cycles from measured tremor data of the subject, said tremor cycles measuring periodic variation in movement of the subject due to the tremor; determining an instantaneous frequency for each tremor cycle and collating the instantaneous frequencies; determining an instantaneous variation between the instantaneous frequencies of each pair of adjacent tremor cycles within the series; comparing the instantaneous variation to the collation of determined instantaneous frequencies to determine a distribution of instantaneous variations; and determining an index value of the distribution of the instantaneous variations, said index value defining the stability of the tremor.

An apparatus for determining balance compensation includes a platform, sensors and a processor. The platform is configured for a person to stand on the platform. The sensors are coupled to the platform and measure at least one of a weight and a pressure. The processor determines a balance of the person based on the measurements of the sensors.

Embodiments regard nutrition assessment using a handheld device. An embodiment of an apparatus includes a handle with a controller within the handle, an attachment arm extending from the handle, and a user-assistive device coupled with an end of the attachment arm, wherein the apparatus is to determine a mass held by the user-assistive device, the determination being made during a task by a user of the handheld tool including manipulation of the handheld tool.

Methods and systems implement a variety of sensors, including in embodiments various combinations of EEG sensors, biochemical sensors, photoplethysmography (PPG) sensors, microphones, and accelerometers, to detect, predict, and/or classify various physiological events and/or conditions related to epilepsy, sleep apnea, and/or vestibular disorders. The events can include neuroelectrical events, cardiac events, and/or pulmonary events, among others. In some cases, the method and systems implement trained artificial intelligence (AI) models to detect, classify, and/or predict. The methods and systems are also capable of optimizing a treatment window, suggesting treatments that may improve the overall well-being of the patient (including improving pre- or post-event symptoms and effects), and/or interacting with various care providers.

A tremor stabilization apparatus, for example for helping to stabilize tremors of user with Parkinson's Disease or Essential Tremor. The tremor stabilization apparatus has a housing that is attachable to a part of a user's body and a rotatable flywheel assembly mounted to the housing. The rotatable flywheel assembly includes a rotatable flywheel, a prime mover arranged to rotate the flywheel about a flywheel rotation axis, and a gimbal to which the flywheel is attached. The gimbal is pivotally mounted to the housing at a hinge formed between the gimbal and the housing and defining a precession axis such that the flywheel can precess with respect to the housing about the precession axis. The precession axis is fixed relative to the housing. The tremor stabilization apparatus further includes a biasing member arranged to oppose precession of the rotatable flywheel assembly and urge the rotatable flywheel assembly to an equilibrium position.

An apparatus for hand tremor stabilization including a rotatable flywheel assembly mountable to a hand of a user. The rotatable flywheel assembly includes i) a flywheel having a flywheel mass, m, and a flywheel diameter, d, and ii) a prime mover adapted to rotate the flywheel at a rotational speed, r, about a flywheel rotation axis such that the rotatable flywheel assembly generates an angular momentum having a magnitude of between about 0.05 kgm2/s and about 0.30 kgm2/s.

Existing wearable device-based approaches to capture a_tremor signal have accuracy limitations due to usage of accelerometer sensor with inherent noisy nature. The method and system disclosed herein taps characteristics of the PPG sensor of being sensitive to the motion artifact, as an advantage, to capture tremor_signals present in the PPG sensor. The method disclosed herein describes an approach to extract tremor_signals of interest from the PPG signal by performing a Singular Spectrum Analysis (SSA) followed by spectrum density estimation. The SSA comprises performing embedding on the acquired PPG signal, performing Principal Component Analysis (PCA) on the embedded signal and reconstructing the rest tremor signal from the significant principal components identified post the PCA. Further, the spectrum density estimation detects a dominant frequency present in the principal components, which is the dominant frequency associated with the rest tremor.

Disclosed is a system for associating a symptom with a medical condition. The system comprises a server arrangement, associated with a user device. The server arrangement is operable to: provide, to user device, a set of user activities; receive, from user device, information relating to selection of a user activity from set of user activities; receive, from user device, user input associated with selected user activity; analyse user input and assign performance score thereto; identify, based on performance score, one or more symptoms; and assign severity score to symptom for associating symptom with medical condition. Disclosed also is method for associating symptom with medical condition and computer program product to execute aforementioned method.

The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subject's movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subject's symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMG) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subject's with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.