Patents by Inventor SIMENG ZHANG
SIMENG ZHANG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240139515Abstract: An example method includes: delivering one or more electrical stimulation pulses to one or more nerves of a patient via one or more inserted electrodes on a lead or formed on an evaluation needle and prior to implantation of an implantable medical device, the one or more nerves being associated with stimulation therapy; sensing an evoked signal generated by one or more signal sources in response to delivery of the one or more electrical stimulation pulses; determining, based at least in part on the evoked signal, a therapy response group of a plurality of therapy response groups for the patient, wherein the therapy response group indicates whether implantation of the implantable medical device is recommended; and outputting information indicative of the determined therapy response group.Type: ApplicationFiled: October 25, 2023Publication date: May 2, 2024Inventors: Katelynn M. Johnson, Simeng Zhang, Julia P. Slopsema, Lisa M. Jungbauer Nikolas, Sarah J. Offutt
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Patent number: 11957913Abstract: The present disclosure provides systems and methods for generating burst waveforms. An implantable neurostimulation system includes an implantable stimulation lead including a plurality of contacts, and an implantable pulse generator communicatively coupled to the stimulation lead. The pulse generator is configured to generate a waveform including a burst that includes a leading anodic pulse followed by alternating cathodic pulses and anodic pulses, each cathodic pulse in the burst having a greater amplitude than the previous cathodic pulse.Type: GrantFiled: May 4, 2023Date of Patent: April 16, 2024Assignee: Advanced Neuromodulation Systems, Inc.Inventors: Simeng Zhang, Hyun-Joo Park, Filippo Agnesi, Yagna Pathak, Erika Ross
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Patent number: 11931572Abstract: A noninvasive/minimally invasive neuromodulation system and method for providing therapy to a target neural tissue of a patient. In one arrangement, an example method comprises applying at least two input waveforms to respective pairs of electrodes affixed on the patient's skin or subcutaneously disposed relative to the target neural tissue, wherein the frequencies of the input waveforms are configured such that they combine, when simultaneously applied, to generate a beat waveform having a beat frequency due to interference. The beat waveform is causative of a transcutaneous/subcutaneous temporal interference (T/STI) electric field generated in the patient body, the T/STI electric field including an interference region at least partially overlapping the target neural tissue of the patient, wherein the beat frequency is of a value operative to impart a therapeutic effect to the target neural tissue.Type: GrantFiled: December 24, 2020Date of Patent: March 19, 2024Assignee: Advanced Neuromodulation Systems, Inc.Inventors: Simeng Zhang, Hyun-Joo Park, Erika Ross
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Publication number: 20230414288Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.Type: ApplicationFiled: September 6, 2023Publication date: December 28, 2023Inventors: Yagna Pathak, Simeng Zhang, Dehan Zhu, Anahita Kyani, Hyun-Joo Park, Erika Ross
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Patent number: 11786309Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.Type: GrantFiled: December 28, 2020Date of Patent: October 17, 2023Assignee: ADVANCED NEUROMODULATION SYSTEMS, INC.Inventors: Yagna Pathak, Simeng Zhang, Dehan Zhu, Anahita Kyani, Hyun-Joo Park, Erika Ross
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Publication number: 20230271014Abstract: The present disclosure provides systems and methods for generating burst waveforms. An implantable neurostimulation system includes an implantable stimulation lead including a plurality of contacts, and an implantable pulse generator communicatively coupled to the stimulation lead. The pulse generator is configured to generate a waveform including a burst that includes a leading anodic pulse followed by alternating cathodic pulses and anodic pulses, each cathodic pulse in the burst having a greater amplitude than the previous cathodic pulse.Type: ApplicationFiled: May 4, 2023Publication date: August 31, 2023Inventors: Simeng Zhang, Hyun-Joo Park, Filippo Agnesi, Yagna Pathak, Erika Ross
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Publication number: 20230240760Abstract: The present disclosure provides systems and methods for estimating an orientation of an implanted deep brain stimulation (DBS) lead. Such methods include generating an initial image dataset, down-sampling a respective image or adding noise to images of the subset of the initial image dataset, and re-slicing at least a subset of the modified image dataset along an alternative primary imaging axis, to generate an integrated image dataset. The method also include partitioning the integrated image dataset into a preliminary training image dataset and a testing image dataset, and re-sizing at least a subset of the preliminary training image dataset with a localized field of view around a depicted DBS lead, to generate a training image dataset. The method further includes training a machine-learning model using the training image dataset, and executing the trained machine-learning model to estimate, during a DBS implantation procedure, an orientation of a subject implanted DBS lead.Type: ApplicationFiled: April 5, 2023Publication date: August 3, 2023Inventors: Yagna Pathak, Hyun-Joo Park, Simeng Zhang, Anahita Kyani, Erika Ross, Dehan Zhu, Douglas Lautner
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Patent number: 11679264Abstract: The present disclosure provides systems and methods for generating burst waveforms. An implantable neurostimulation system includes an implantable stimulation lead including a plurality of contacts, and an implantable pulse generator communicatively coupled to the stimulation lead. The pulse generator is configured to generate a waveform including a burst that includes a leading anodic pulse followed by alternating cathodic pulses and anodic pulses, each cathodic pulse in the burst having a greater amplitude than the previous cathodic pulse.Type: GrantFiled: October 28, 2020Date of Patent: June 20, 2023Assignee: ADVANCED NEUROMODULATION SYSTEMS, INC.Inventors: Simeng Zhang, Hyun-Joo Park, Filippo Agnesi, Yagna Pathak, Erika Ross
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Patent number: 11648063Abstract: The present disclosure provides systems and methods for estimating an orientation of an implanted deep brain stimulation (DBS) lead. Such methods include generating an initial image dataset, down-sampling a respective image or adding noise to images of the subset of the initial image dataset, and re-slicing at least a subset of the modified image dataset along an alternative primary imaging axis, to generate an integrated image dataset. The method also include partitioning the integrated image dataset into a preliminary training image dataset and a testing image dataset, and re-sizing at least a subset of the preliminary training image dataset with a localized field of view around a depicted DBS lead, to generate a training image dataset. The method further includes training a machine-learning model using the training image dataset, and executing the trained machine-learning model to estimate, during a DBS implantation procedure, an orientation of a subject implanted DBS lead.Type: GrantFiled: December 7, 2020Date of Patent: May 16, 2023Assignee: Advanced Neuromodulation Systems, Inc.Inventors: Yagna Pathak, Hyun-Joo Park, Simeng Zhang, Anahita Kyani, Erika Ross, Dehan Zhu, Douglas Lautner
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Publication number: 20230146551Abstract: In some embodiments, a method of providing a neurostimulation therapy to a patient, comprises: generating a noise pulse pattern defining a pulse train of pulses to be generated according to a noise profile in an external device; communicated the generated noise pulse pattern to an implantable pulse generator (IPG) of a patient; generating, by the IPG, a series of pulses in sequence for noise stimulation of the patient using the noise pulse pattern from the external device, wherein the IPG applies one or more randomization operations to the pulse pattern from the external device without expanding memory storage for the pulse pattern while maintaining the noise profile of the pulse pattern from the external device; and applying the series of pulses in sequence to neural tissue of the patient using one or more electrodes of one or more stimulation leads.Type: ApplicationFiled: November 3, 2022Publication date: May 11, 2023Inventors: Hyun-joo Park, Simeng Zhang, Ameya Nanivadekar, Yagna Pathak
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Publication number: 20230055984Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230054076Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Plano Zhu
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Publication number: 20230053982Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Naivadekar, Dehan Zhu
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Publication number: 20230054906Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230053914Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230054261Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230053428Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Simeng Zhang, Yagna Pathak, Hyun-Joo Park
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Publication number: 20230059718Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230054788Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu
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Publication number: 20230056291Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.Type: ApplicationFiled: August 18, 2022Publication date: February 23, 2023Inventors: Mary Khun Hor-Lao, Binesh Balasingh, Scott DeBates, Douglas Alfred Lautner, Yagna Pathak, Simeng Zhang, Diane Whitmer, Anahita Kyani, Hyun-Joo Park, Erika Ross, David Page, Ameya Nanivadekar, Dehan Zhu