The present disclosure provides methods for diagnosing and determining the disease progression of neurodegenerative disorders in patients using neurophysiological biomarkers.

Disclosed is a method for diagnosing a neurodegenerative disease in a subject. The method comprises obtaining from the subject a sample comprising at least one live blood cell, and optionally isolating at least one live blood cell from the sample. The method further comprises generating one or more multispectral or hyperspectral images of the at least one cell, and analysing spectral characteristics of autofluorescence from the at least one cell. Also disclosed is a system configured to aid in the detection or diagnosis of a neurodegenerative disease. Also disclosed is a method for selecting a subject for treatment for a neurodegenerative disease. Also disclosed is a method for monitoring the response of a subject to a therapeutic treatment for a neurodegenerative disease. Also disclosed is a protocol for monitoring the efficacy of a therapeutic treatment for a neurodegenerative disease.

Medical device systems and methods are disclosed herein for assessing motor symptoms in Parkinson's disease patients through passively and/or actively acquired sensor data of motor behaviors and generating motor system assessments. Passive movement data and/or active motor performance data collected from Parkinson's disease patients is representative of EQ-5D-5L, PDQ-39, and/or MDS-UPDRS health status measurement data to more accurately predict quality of life, health status, and disease severity of Parkinson's disease patients. The generated motor system assessment may be used to provide neurologists and other health professionals with more accurate treatment recommendations and disease management protocols rather than using patient surveys alone.

The present disclosure relates to: a method for evaluating a state of a motor function of a patient who has or is suspected of having brain damage by using parameters obtained from a diffusion weighted image of the patient's brain; a program for executing the method in a computer; and an image processing device and an MRI device which can be used in practicing the method. According to the present disclosure, the motor function state of a patient who has or is suspected of having brain damage can be evaluated, and it is also possible to predict the recovery of the motor function after regeneration treatment. Accordingly, whether the patient is suitable for the regeneration treatment can be determined before the start of the treatment.

The present invention presents a device for calculating, during one step or each successive step of the gait of a subject, the push-off P.sub.0 of the subject, which is the power per kilogram released by the ankle push-off moment, which comprises: at least one inertial measurement unit (1A, 1B) on one foot of the subject, the inertial measurement unit (1A, 1B) having: at least one accelerometer to measure the vertical and antero-posterior accelerations and/or at least one gyroscope to measure the medic-lateral angular speed data {acute over (α)} during the gait, storage and calculation means (2A) connected to the Inertial measurement unit (1A, 1B), configured to calculate: for the foot, and for the step or each successive step of the gait:—the time of the heel-off and the time of the toe-off,—the push-off P.sub.0, by the Euler's equation stating that the sum of moments acting on the foot taken as a rigid body, being equal to the rate of change of the angular momentum of the foot, with the calculation of the push-off P.sub.0 at the time of the toe-off where the sagittal angular momentum is at its maximum in absolute value, displaying means (2B) connected to the storage and calculation means (2A).

The abnormal data processing system is provided with: a storage unit for holding a multiple-subject DB in which data on multiple subjects are accumulated and individual-subject DB in which data on individual subjects are accumulated; an individual-subject DB divergence-degree calculation unit for calculating an individual-subject DB divergence degree which is the degree of divergence of the new data from the individual-subject DB; a multiple-subject DB divergence degree calculation unit for calculating a multiple-subject DB divergence degree which is the degree of divergence of the new data from the multiple-subject DB; and a composite divergence degree calculation unit for determining a composite divergence by compositing the individual-subject DB divergence degree and the multiple-subject DB divergence degree using the number of data instances in the individual-subject DB. The abnormal data processing system determines whether or not the new data is abnormal on the basis of the composite divergence degree.

A method and user device for providing a unified Parkinson's disease rating scale (UPDRS) value by a user device includes generating, by a sensor of the user device, sensor data based on a user of the user device manipulating the user device. The UPDRS value is determined based on the sensor data and a deep neural network (DNN) model. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

A system for monitoring the state of a disease or the state of a person using a biomarker, the system comprising: a motion data obtaining unit configured to obtain from at least one motion sensor motion data from a person having the disease, a generating unit configured to generate a value of the biomarker of the disease based on the obtained motion data, and an assessing unit configured to assess the value of the biomarker of the disease and, based on the assessment, to output information related to the state of the disease or state of a person

Embodiments may provide multimodal diagnostic systems and methods for detecting neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), depression, PTSD, schizophrenia, dementia and many others. For example, a system for monitoring brain activity may comprise a plurality of sensors, each adapted to monitor a physical or physiological parameter and output a signal representing the monitored physical or physiological parameter, wherein the plurality of sensors includes at least one sensor configured to monitor a brain activity parameter, a data collection device adapted to receive the plurality of signals from the plurality of sensors and to process the signals to form digital data representing the monitored physical or physiological parameters, and a data processing device adapted to process digital data representing the monitored physical or physiological parameters to determine presence of a neurological disorder or condition.

A writing instrument that includes a writing element for depositing a writing material on a support and a plurality of sensors including at least a force sensor and a movement sensor, a communication unit that exchanges data with a remote device a control unit connected to the sensors and to the communication unit in order to transmit to the remote device the measurements provided by the sensors, a memory unit connected to the control unit that stores one or more measurements from the sensors; and a hollow casing that contains at least part of the writing element so that the writing end is exposed, and also houses the sensors, the control unit, the memory unit and the communication unit.