A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Embodiments may provide self-guided, self-directed diagnostics and treatment of neural conditions. For example, a system may comprise a processor, memory accessible by the processor, and program instructions and data stored in the memory, a plurality of stimulation devices connected to signal output circuitry interfacing the processor with the stimulation devices, program instructions and data to control the stimulation devices to generate and transmit stimulation signals, a plurality of sensing devices connected to signal input circuitry interfacing the processor with the sensing devices, program instructions and data to receive sensed signals from the sensing devices, a communication device adapted to wirelessly communicate with a server computer system, and program instructions and data to perform dynamic closed loop feedback of the stimulation signals based on the received sensed signals to provide self-guided, self-directed diagnostics and treatment of neural conditions using at least one recipe for a treatment strategy guided by artificial intelligence.

A hand-held sized ocular and neurological screening device, system and method, the screening device comprising an eyepiece and a hand-held housing, the housing comprising a tubular stimulus chamber defining a light stimulus channel, wherein an illumination source is configured to provide light stimulus towards an opening through the light stimulus channel and an operational chamber comprising an infrared camera positioned outside the stimulus channel and inclined towards the opening, the infrared camera is configured to capture images of the pupils and eye movements through the opening without interfering with the light stimulus and a controller configured to receive the captured images from the infrared camera. The hand-held sized device can include a clip-on fixture for fixing the device onto a table, a desktop, or any portable ophthalmic apparatus.

Embodiments of the presently-disclosed subject matter include methods and systems for measuring a level of a neurotransmitter in a subject. Embodiments of the present methods comprise displaying a fixation point, a reward target, and a non-reward target, and measuring one or more saccade movement parameters for reward saccades and non-reward saccades. The saccade movement parameters can include velocity, amplitude, reaction time, or a combination thereof. The present methods can further include determining a reward modulation of the subject, the reward modulation being equal to a difference between the reward and the non-reward values for a respective saccade movement parameter. Some embodiments further include identifying the subject as including a deficiency of the neurotransmitter if there is a statistically measurable difference between the reward modulation of the subject and a reference reward modulation and/or if the non-reward and the reward saccade movement parameters are statistically equivalent.

The present disclosure provides an operating method of a dopamine transporter check system, and the operation method includes steps as follows. A scan image of a subject's brain is obtained from a scan machine, and the scan image is a three-dimensional image. The scan image is aligned to a standard brain space to obtain a standardized scan image. Intensity normalization is performed on the standardized scan image. The standardized scan image after the intensity normalization is converted into a two-dimensional image. A plurality of image data are got from at least one region of interest in the two-dimensional image, and the at least one region of interest includes a left caudate, a left putamen, a right caudate and a right putamen. A dopamine neuron loss degree measurement and evaluation model based on the image data is established through a transfer learning.

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.

The present invention relates to a digital content-based method for providing therapeutics information, the method comprising: a first step of performing stimulation on a brain of a user to obtain fNIRS (functional near-infrared spectroscopy) data of the user; a second step of extracting a first brain activation area from a plurality of brain areas of the user using the obtained fNIRS data; a third step of determining a first brain state of the user, based on the first brain activation area; a fourth step of providing the user with a content determined corresponding to the first brain state determined in the third step under an XR (Extended Reality) environment; a fifth step in which the user performs a mission corresponding to the content; a sixth step of extracting a second brain activation area from the plurality of brain areas with reference to the fNIRS data of the user following performing the mission; and a seventh step of determining a second brain state of the user, based on the second brain activation area; an eighth step of determining information related to amelioration of the brain state of the user.

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.

A method for facilitating a Parkinson's Disease (“PD”) assessment of a patient includes capturing first video of a patient performing first test movements while holding the mobile device; capturing second video of the patient performing second test movements while maintaining the mobile device on their person; capturing third video of the patient performing third test movements including standing and walking; capturing one or more IMU readings using an IMU of the mobile device; processing the first video, the second video, and the third video according to (i) a hand landmark model to generate one or more hand biomarkers, (ii) a face landmark model to generate one or more face biomarkers, and (iii) a body landmark model to generate one or more body biomarkers; and determining an assessment score based on a standardized PD assessment by processing the biomarkers.