33 results about "Digital organism" patented technology

Medical sensing devices and systems that transmit digital data from a first device via an ultrasonic digital modem to a receiver such as a smartphone. Methods of transmitting digital biological data by ultrasound are also described.

The system described herein collects patient data passively and non-passively via onboard and external sensors, and combines the data with past clinical history to generate digital biomarkers. The collected data can also be further combined with other data generating systems to more accurately predict disease exacerbations. The system monitors the digital biomarkers in real-time, and can detect a change in the disease state prior to clinical decompensation and suggest pre-emptive intervention. The system enables a patient to be treated early in the clinical timeline when the disease exacerbation is at the subclinical level rather than waiting until the disease exacerbation reaches the clinical level. Acting when the exacerbation is at the subclinical level enables preemptive treatment rather than reactive treatment, which is often more cost effective while improving clinical outcomes. The system is able to make the predictions by detecting subclinical changes in digital biomarkers that are generated from respiratory, cardiac, patient reported symptoms, user behaviors, and environmental triggers.

A system and method for evaluating the effectiveness of a medical treatment and predicting future medical issues is provided. A digital set of biometric data comprising a plurality of biometric data points is received and stored in a digital database. The digital set of biometric data is analyzed to determine its relative volatility. The relative volatility is then evaluated to help determine the effectiveness of a medical treatment and predict future medical issues.

Devices and methods are disclosed for use and processing of patient geolocation data in order to objectively determine a patient's territory as an artificially created digital biomarker while maintaining locational privacy. The objective determination of a patient's territory, defined as the area traversed in a specific time interval, can be used as a measurement of quality of life, as well as socio-economic contribution and benefit. Devices and methods are also disclosed for creating an artificial Overall Territory Activity Digital Biomarker based on Patient Activity Factors in addition to the Patient Territory Digital Biomarker, and which Overall Territory Activity Digital Biomarker also maintains locational data privacy. Furthermore, devices and methods are disclosed for capturing and transmitting digital biospecimens, the transformed geolocation data used to determine the Patient Territory Digital Biomarker. The digital biospecimen data can be subsequently used to create alternative, data privacy-preserving determinations of Patient Territory Digital Biomarkers, Patient Activity Factors, and / or Overall Territory Activity Digital Biomarkers.

The present invention extends to methods, systems, and computer program products for forecasting mood changes from digital biomarkers and more generally for forecasting changes in a neuropsychological clinical assessment. User interaction data indicative of a user's interaction with a mobile device is passively captured over a period of time and can include keyboard timings. A function mapping is executed to compute a digital biomarker for a brain health metric from the captured user interaction data. A prior digital biomarker for the brain health metric (computed from previously captured user interaction data by executing the function mapping) is accessed. A difference is detected between the digital biomarker and the prior digital biomarker. A change in a score of the neuropsychological test score is forecast to occur within a specified time range in the future based on the detected differences. The forecast change is output.

The present invention extends to methods, systems, and computer program products for forecasting mood changes from digital biomarkers and more generally for forecasting changes in a neuropsychological clinical assessment. User interaction data indicative of a user's interaction with a mobile device is passively captured over a period of time. A function mapping (modeling a neuropsychological test for a brain health metric) is executed to compute a digital biomarker for a brain health metric from the captured user interaction data. A prior digital biomarker for the brain health metric (computed from previously captured user interaction data by executing the function mapping) is accessed. A difference is detected between the digital biomarker and the prior digital biomarker. A change in a score of the neuropsychological test score is forecast to occur within a specified time range in the future based on the detected differences. The forecast change is output.

A locomotion generation method for a digital creature includes: imaging and capturing movements of a creature placed on a base plate having a printed pattern; extracting body position information, body posture information, leg posture information, and footprint information of the creature by analyzing captured images; and generating creature movement by applying inverse kinematics to the body position information, the body posture information, the leg posture information, and the footprint information of the creature. The movements of the creature are imaged and captured by using two or more cameras without camera calibration

The present disclosure relates to the field of diagnostics, specifically, to a method of identifying progressing multiple sclerosis (MS) in a subject. At least one performance parameter is determined from a dataset of activity measurements obtained from the subject using a mobile device, and the performance parameter is compared to a reference, whereby a subject with progressing MS will be identified. Also disclosed is a method of recommending an anti-CD20 antibody therapy against MS that includes the steps just mentioned and the further step of recommending the anti-CD20 antibody therapy if the subject suffers from progressing MS. Also disclosed is a mobile device having a processor, at least one sensor and a database as well as software which is tangibly embedded to the device and, when running on said device, carries out the method of this disclosure as well as the use of such a device for identifying a subject suffering from progressing MS.

The invention proposes a machine learning system (110) for determining at least one analytical model for predicting at least one target variable indicative of a disease state. The machine learning system (110) comprises:-at least one communication interface (114) configured for receiving input data, where the input data comprises a set of historical digital biomarker feature data, wherein the set of historical digital biomarker feature data comprises a plurality of measured values indicative of the disease state to be predicted; -at least one model unit (116), said at least one model unit comprising at least one machine learning model, said at least one machine learning model comprising at least one algorithm; -at least one processing unit (112), where the processing unit (112) is configured for determining at least one training data set and at least one test data set from an input data set, where the processing unit (112) is configured for determining the analysis model by training the machine learning model with the training data set, wherein the processing unit (112) is configured to predict a target variable for the test data set using the determined analysis model, and wherein the processing unit (112) is configured to determine a performance of the determined analysis model based on the predicted target variable and a truth value of the target variable of the test data set.

The present invention relates to the field of diagnostics. More specifically, it concerns a method for assessing a cognition and movement disease or disorder in a subject suspected to suffer therefromcomprising the steps of determining at least one cognition and / or fine motoric activity parameter from a dataset of cognition and / or fine motoric activity measurements obtained from said subject using a mobile device and comparing the determined at least one cognition and / or fine motoric activity parameter to a reference, whereby the cognition and movement disease or disorder will be assessed. The present invention also relates to a method for identifying whether a subject will benefit from a therapy for a cognition and movement disease or disorder comprising the steps of the method of the aforementioned invention and the further step of identifying the subject as a subject that benefits from the therapy if the cognition and movement disease or disorder is assessed. The present inventioncontemplates a mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out themethod of the present invention, a system comprising a mobile device comprising at least one sensor and a remote device comprising a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method and the use of the mobile device or system according to the invention for assessing a cognition and movement disease or disorder in a subject.

The invention relates to a digital biological system for simulating a biological competition and evolution process. According to one aspect of the invention, the process from birth, reproduction, variation, competition among individuals to death of a biological individual is simulated by programs, and each single program represents a biological individual. Once a parent program is started, the duplicate child programs can be initialized and die automatically; as the individuals are different in the execution times for implementing a certain loop command before child duplication and the CPU (central processing unit) processing time to be consumed, different competitive advantage degrees are formed among different programs, and the numbers of the reproduced child programs are different as well. By setting different parameters, the programs can simulate different variant children and simulate the competition as well as the evolution process of selecting the superior and eliminating the inferior of biological individuals, thereby providing a new experiment tool of a bionic model.

Currently, assessing the severity and progression of symptoms in a subject diagnosed with a muscular disability, in particular SMA involves in-clinic monitoring and testing of the subject every 6 to 12 months. However, monitoring and testing a subject more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the subject. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the subject outside of a clinic environment as described herein provides advantages in cost, ease of monitoring and convenience to the subject. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing of the axial motor function of a subject having a muscular disability, in particular SMA by active testing of the subject.

The present invention relates to the field of disease tracking and potentially even diagnostics. Specifically, it relates to a method of assessing a muscular disability and, preferably, spinal muscular atrophy (SMA) in a subject comprising the steps of determining at least one performance parameter from a dataset of pressure measurements of the individual finger strength from said subject using amobile device, and comparing the determined at least one performance parameter to a reference, whereby the muscular disability and, preferably, SMA will be assessed. The present invention also relatesto a mobile device comprising a processor, at least one pressure sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out themethod of the invention as well as the use of such a device for assessing a muscular disability and, preferably, SMA.

Currently, assessing the severity and progression of symptoms in a subject diagnosed with a muscular disability, in particular SMA involves in-clinic monitoring and testing of the subject every 6 to 12 months. However, monitoring and testing a subject more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the subject. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the subject outside of a clinic environment as described herein provides advantages in cost, ease of monitoring and convenience to the subject. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing of the distal motor function of a subject having a muscular disability, in particular SMA by active testing of the subject.

The present invention relates to the field of diagnostics. Specifically, the invention relates to a method of identifying progressing multiple sclerosis (MS) in a subject, and the method includes thesteps of determining at least one performance parameter determined from a dataset of activity measurements obtained from said subject using a mobile device, and comparing the determined at least one performance parameter to a reference, whereby a subject with progressing MS will be identified. Moreover, encompassed by the present invention is a method of recommending an anti-CD20 antibody therapyagainst MS comprising the steps of the method of the present invention and the further step of recommending the anti-CD20 antibody therapy if the subject suffers from progressing MS. The present invention also relates to a mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carriesout the method, and to the use of such a device for identifying a subject suffering from progressing MS.

Currently, assessing the severity and progression of symptoms in a subject diagnosed with a muscular disability, in particular SMA involves in-clinic monitoring and testing of the subject every 6 to 12 months. However, monitoring and testing a subject more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the subject. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the subject outside of a clinic environment as described herein provides advantages in cost, ease of monitoring and convenience to the subject. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing of the axial motor function of a subject having a muscular disability, in particular SMA by active testing of the subject.

A method of diagnosis based on biomarker and apparatus for performing the method includes receiving, by a diagnosis server, digital biomarker data from user equipment, generating, by the diagnosis server, basic diagnostic data on the basis of the digital biomarker data and generating, by the diagnosis server, diagnostic result data on the basis of the basic diagnostic data.

An EWOD device and a related method of performing a digital biological assay are described that employs two volume measurements for enhanced assay determination. The method includes partitioning a sample reservoir and measuring the volume of each partition; initiating a biological assay wherein the biological assay includes measuring a partition property and a volume of each partition in real time as part of determining a concentration of the product substance in each partition based on the measured partition property and volume; and categorizing the partitions by a number of biological entities contained in each partition from which the number of biological entities may be calculated, which in turn may be used to calculate the total number of biological entities or concentration in the sample reservoir. The method further may include an enhanced partitioning process that minimizes variation in the volume of the partitions.

Currently, assessing the severity and progression of symptoms in a patient diagnosed with Alzheimer's disease involves in-clinic monitoring and testing of the patient every 6 to 12 months. However, monitoring and testing a patient more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the patient. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the patient outside of a clinic environment as described herein provides advantages in cost, ease of monitoring, ecological validity, reliability and convenience to the patient, like improvement of quality of life. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing one or more pre-clinical signs and / or symptoms of Alzheimer's disease in a patient by passive monitoring of the patient and / or active testing of the patient.

Embodiments of the present disclosure relate to systems and methods for detecting cognitive decline of a subject by using the passively obtained data from at least one mobile device. In an exemplary embodiment, a computer-implemented method comprises receiving the passively obtained data from at least one mobile device. The method further comprises generating the digital biomarker data from the passively obtained data. The method further comprises analyzing the digital biomarker data to determine whether the subject is exhibiting signs of cognitive decline.

The invention relates to a digital biopotential acquisition system with 8 channels. In particular, the present invention relates to a biocompatible recording system for acquiring electronic information from the nervous system of a living being, said biocompatible recording system comprising a preamplifier stage and a further amplifier stage, wherein the second amplifier an input of a stage coupled to the output of the preamplifier; and a low pass filter having a capacitance multiplier connected to the amplifier of the second stage. The preamplifier of the recording system is designed using P-MOS technology.

A system for predicting the onset of a physiological condition of a subject combines an in-vitro subject model having input parameters relating to actual or predicted external stimuli to which the subject is or may be exposed and an in-silico model. The in-vitro model outputs subject-specific parameters which are not being monitored, or cannot be monitored, in-vivo. The in-silico subject model uses subject-specific parameters to predict the response of the subject to the actual or predicted external stimuli and thereby predict an onset of a physiological condition of the subject.

Currently, assessing the severity and progression of symptoms in a subject diagnosed with a muscular disability, in particular SMA involves in-clinic monitoring and testing of the subject every 6 to 12 months. However, monitoring and testing a subject more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the subject. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the subject outside of a clinic environment as described herein provides advantages in cost, ease of monitoring and convenience to the subject. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing of the axial motor function of a subject having a muscular disability, in particular SMA by active testing of the subject.

Currently, assessing the severity and progression of symptoms in a subject diagnosed with a muscular disability, in particular SMA involves in-clinic monitoring and testing of the subject every 6 to 12 months. However, monitoring and testing a subject more frequently is preferred, but increasing the frequency of in-clinic monitoring and testing can be costly and inconvenient to the subject. Thus, assessing the severity and progression of symptoms via remote monitoring and testing of the subject outside of a clinic environment as described herein provides advantages in cost, ease of monitoring and convenience to the subject. Systems, methods and devices according to the present disclosure provide a diagnostic for assessing of the motor function of a subject having a muscular disability, in particular SMA by active testing of the subject.

Aspects described herein relate to the field of disease tracking and diagnosis. Specifically, these aspects relate to a method of assessing muscle dysfunction and in particular spinal muscular atrophy (SMA) in a subject, the method comprising the steps of determining at least one parameter of a sensor measurement dataset from the subject using a mobile device, and comparing the determined at least one parameter with a reference, as a result, the muscle disability, in particular SMA, will be evaluated. Aspects described herein also relate to a mobile device comprising a processor, at least one pressure sensor and a database, and software tangibly embedded in the device and performing the method of the invention when running on the device; and the use of such a device for assessing muscle disability and in particular SMA.