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公开(公告)号：US11347221B2
公开(公告)日：2022-05-31
申请号：US16661637
申请日：2019-10-23
摘要： A method of training an artificial neural network having a series of layers and at least one weight matrix encoding connection weights between neurons in successive layers. The method includes receiving, at an input layer of the series of layers, at least one input, generating, at an output layer of the series of layers, at least one output based on the at least one input, generating a reward based on a comparison of between the at least one output and a desired output, and modifying the connection weights based on the reward. Modifying the connection weights includes maintaining a sum of synaptic input weights to each neuron to be substantially constant and maintaining a sum of synaptic output weights from each neuron to be substantially constant.
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2.发明申请公开(公告)号：US20180264264A1
公开(公告)日：2018-09-20
申请号：US15983629
申请日：2018-05-18
CPC分类号： A61N1/36025 , A61M21/00 , A61M2021/0072 , A61M2205/52 , A61M2230/10 , A61N1/025 , A61N1/0484 , A61N1/36034 , G16H20/30 , G16H20/70
摘要： Described is a system for transcranial stimulation to improve cognitive function. During operation, the system generates a customized stimulation pattern based on damaged white matter. Further, data is obtained representing natural brain oscillations of a subject. Finally, while the subject is awake, one or more electrodes are activated in phase with the natural brain oscillations and based on the customized stimulation pattern.
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公开(公告)号：US20180146916A1
公开(公告)日：2018-05-31
申请号：US15875591
申请日：2018-01-19
CPC分类号： A61B5/4812 , A61B5/04012 , A61B5/0482 , A61N1/36025 , A61N1/36092 , A61N1/36139
摘要： Described is a system for memory improvement intervention. Based on both real-time EEG data and a neural model, the system simulates replay of a person's specific memory during a sleep state. Using the neural model, a prediction of behavioral performance of the replay of the specific memory is generated. If the prediction is below a first threshold, then using a memory enhancement intervention system, the system applies an intervention during the sleep state to improve consolidation of the specific memory. If the prediction is below a second threshold, the system reduces the intervention performed using the memory enhancement intervention system.
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4.发明申请公开(公告)号：US20200026287A1
公开(公告)日：2020-01-23
申请号：US16519814
申请日：2019-07-23
发明人： Qin Jiang , Youngkwan Cho , Nigel D. Stepp , Steven W. Skorheim , Vincent De Sapio , Praveen K. Pilly , Ruggero Scorcioni
摘要： Described is a system for online vehicle recognition in an autonomous driving environment. Using a learning network comprising an unsupervised learning component and a supervised learning component, images of moving vehicles extracted from videos captured in the autonomous driving environment are learned and classified. Vehicle feature data is extracted from input moving vehicle images. The extracted vehicle feature data is clustered into different vehicle classes using the unsupervised learning component. Vehicle class labels for the different vehicle classes are generated using the supervised learning component. Based on a vehicle class label for a moving vehicle in the autonomous driving environment, the system selects an action to be performed by the autonomous vehicle, and causes the selected action to be performed by the autonomous vehicle in the autonomous driving environment.
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公开(公告)号：US11899839B1
公开(公告)日：2024-02-13
申请号：US17965566
申请日：2022-10-13
发明人： Steven W. Skorheim , Tiffany Hwu
摘要： Described is a system for multimodal machine-aided comprehension analysis. The system can be implemented in an augmented reality headset that, in conjunction with a processor, generates an initial scene graph of a scene proximate the user. Items and labels are presented, with the headset tracking eye movements of the user as the user gazes upon the subject labels, item labels, and relationship labels. A resulting scene graph (having relationship triplets) is generated based on the eye movements of the user and an amount of time the user spends gazing upon each of the display components. A comprehension model is generated by estimating a user's comprehension of the relationship triplets, with a knowledge model being generated based on a known knowledge graph and the comprehension model. Cues are then presented to the user based on the comprehension and knowledge models to assist the user in their comprehension of the scene.
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公开(公告)号：US10918862B1
公开(公告)日：2021-02-16
申请号：US16100184
申请日：2018-08-09
摘要： Described is a system for adaptable neurostimulation intervention. The system monitors a set of neurophysiological signals in real-time and updates a physiological and behavioral model. The set of neurophysiological signals are classified in real-time based on the physiological and behavioral model. A neurostimulation intervention schedule is generated based on the classified set of neurophysiological signals. The system activates electrodes via a neurostimulation intervention system to cause a timed neurostimulation intervention to be administered based on the neurostimulation intervention schedule. The neurostimulation intervention schedule and timed neurostimulation intervention are refined based on new sets of neurophysiological signals.
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公开(公告)号：US10736561B2
公开(公告)日：2020-08-11
申请号：US15875591
申请日：2018-01-19
IPC分类号： A61B5/04 , A61B5/00 , A61B5/0482 , A61N1/36
摘要： Described is a system for memory improvement intervention. Based on both real-time EEG data and a neural model, the system simulates replay of a person's specific memory during a sleep state. Using the neural model, a prediction of behavioral performance of the replay of the specific memory is generated. If the prediction is below a first threshold, then using a memory enhancement intervention system, the system applies an intervention during the sleep state to improve consolidation of the specific memory. If the prediction is below a second threshold, the system reduces the intervention performed using the memory enhancement intervention system.
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公开(公告)号：US11926334B1
公开(公告)日：2024-03-12
申请号：US17242164
申请日：2021-04-27
发明人： Tiffany Hwu , David J. Huber , Steven W. Skorheim , Jaehoon Choe
摘要： Described is a system for human-machine teaching for vehicle operation. The system determines currently enabled status reporting modes on a vehicle interface of a vehicle. The currently enabled status reporting modes are compared to a set of preferred status reporting modes of previous users. Based on the comparison, a status reporting mode is selected. A current operational status of the vehicle is reported to a current user, via the vehicle interface, using the selected status reporting mode. The system then determines preferred solutions of previous users to address the current operational status of the vehicle. Suggestions to address the current operational status of the vehicle based on the preferred solutions are reported to the user via the vehicle interface. A vehicle action corresponding to a solution selected by the current user is implemented via a vehicle component.
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9.发明授权公开(公告)号：US11199839B2
公开(公告)日：2021-12-14
申请号：US16519814
申请日：2019-07-23
发明人： Qin Jiang , Youngkwan Cho , Nigel D. Stepp , Steven W. Skorheim , Vincent De Sapio , Praveen K. Pilly , Ruggero Scorcioni
摘要： Described is a system for online vehicle recognition in an autonomous driving environment. Using a learning network comprising an unsupervised learning component and a supervised learning component, images of moving vehicles extracted from videos captured in the autonomous driving environment are learned and classified. Vehicle feature data is extracted from input moving vehicle images. The extracted vehicle feature data is clustered into different vehicle classes using the unsupervised learning component. Vehicle class labels for the different vehicle classes are generated using the supervised learning component. Based on a vehicle class label for a moving vehicle in the autonomous driving environment, the system selects an action to be performed by the autonomous vehicle, and causes the selected action to be performed by the autonomous vehicle in the autonomous driving environment.
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10.发明授权公开(公告)号：US10850099B2
公开(公告)日：2020-12-01
申请号：US15983629
申请日：2018-05-18
摘要： Described is a system for transcranial stimulation to improve cognitive function. During operation, the system generates a customized stimulation pattern based on damaged white matter. Further, data is obtained representing natural brain oscillations of a subject. Finally, while the subject is awake, one or more electrodes are activated in phase with the natural brain oscillations and based on the customized stimulation pattern.
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