Abstract: This invention is directed to a corrosion resistant permanent magnet, to a method for producing a corrosion resistant permanent magnet, and to an intravascular blood pump comprising the magnet. The magnet is corrosion resistant due to a composite coating comprising a metal layer, optionally a metal oxide layer, a layer formed from poly(2-chloro-p-xylylene), and a linker layer between the metal oxide layer and the poly(2-chloro-p-xylylene) layer.

Abstract: The embodiments set forth a technique implemented by a computing device. The technique includes the steps of (1) receiving one or more characteristics associated with a user, wherein the one or more characteristics comprise personal information, performance information, measurement information, cohort information, familial information, comorbidity information, healthcare professional information, or some combination thereof; (2) determining, based on the one or more characteristics, one or more conditions of the user, wherein the one or more conditions pertain to cardiac health, pulmonary health, bariatric health, oncologic health, cardio-oncologic health, or some combination thereof; (3) based on the one or more conditions, identifying, using one or more trained machine learning models, one or more subgroups to present via the display, wherein the one or more subgroups represent different partitions of the one or more characteristics; and (4) presenting, via the display, the one or more subgroups.

Abstract: In one embodiment, a computer-implemented system includes a treatment apparatus configured to be manipulated by a user while performing an exercise session, patient interfaces associated with users, and a server computing device configured to receive treatment data pertaining to the user, determine whether at least one characteristic of the user matches at least one second characteristic of a second user, where the second user belonging to a cohort. Responsive to determining the at least one characteristic of the user matches the at least one second characteristic of the second user, the server computing device is configured to assign the user to the cohort and select, via a trained machine learning model, a treatment plan for the user. Responsive to transmitting a signal to the patient interfaces of users in the cohort, the server computing device enables the patient interfaces to establish the virtual shared session between the patient interfaces.

Abstract: Systems, methods, and apparatuses monitor mammal conditions, report condition changes, and provide neurocode-based treatment in response to condition changes. A mammal implantable controller includes modules to monitor, wirelessly communicate to external computers, and administer treatment received from a remote computer based on monitoring of changes in mammal condition as analyzed by the remote computer. External computers can be provided in the form of a mobile device (e.g., smartphone/tablet), resident treatment pods, and treatment servers. Treatment can be provided to change biological function or trigger cell death in cancer cells.

Abstract: A computer-implemented system includes an assistant interface for providing remote medical assistance to aid a patient in performing various aspects of a rehabilitation regimen for a body part comprising a joint, a bone, or a muscle group. The assistant interface is configured to communicate, via a network connection, a telemedicine signal with the patient interface. The telemedicine signal is configured to control the patient interface and/or a treatment apparatus configured to be manipulated by the patient to perform the rehabilitation regimen. The patient interface and the treatment apparatus are at a patient location geographically separate from a location of the assistant interface. The telemedicine signal includes one or more of an audio signal, an audiovisual signal, an interface control signal for controlling a function of the patient interface, and/or an apparatus control signal for changing an operating parameter of the treatment apparatus.

Abstract: Fast recovery electrocardiogram (ECG) signal method and apparatus are provided. In one embodiment, an ECG apparatus includes an input for receiving a biometric cardiogram signal, such as a Wilson Central Terminal (WCT) signal, and a combiner, such as an adder, for producing a compensated signal. Processing circuitry produces an ECG reflective of the compensated signal and also outputs a signal corresponding to high frequency response of the compensated signal to compensate for low response of the biometric cardiogram signal to high frequency spikes. A resultant ECG is produced by the processing circuitry having pacing signal contribution within the biometric cardiogram signal cancelled.

Abstract: A medical device may comprise an instrument comprising a shaft and a working end comprising a jaw mechanism, and a translating mechanism moveable in a first direction and a second direction relative to the jaw mechanism, the first and second directions opposite to one another. The medical device may further comprise a controller configured to in response to a first input, control movement of the translating mechanism from a proximal position to an intermediate position relative to the jaw mechanism, in response to a second input, control movement of the translating mechanism from the intermediate position to a distal position relative to the jaw mechanism, control movement of the translating mechanism from the distal position back to the proximal position, and monitor a position of the translating mechanism to determine whether the translating mechanism has moved from the distal position back to the proximal position after a predetermined time period.

Abstract: This disclosure is directed to techniques for identifying false detection of asystole in a cardiac electrogram that include determining whether at least one of a plurality of false asystole detection criteria are satisfied. In some examples, the plurality of false asystole detection criteria includes a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarizations in the cardiac electrogram, and a second false asystole detection criterion for detecting decaying noise in the cardiac electrogram.

Abstract: A computer-implemented system includes a treatment apparatus manipulated by a patient while performing an exercise session and a patient interface that receives a virtual avatar. The patient interface presents the virtual avatar. The virtual avatar uses a virtual representation of the treatment apparatus to guide the patient through an exercise session. A server computing device provides the virtual avatar of the patient to the patient interface and receives a message pertaining to a trigger event. The message includes a severity level of the trigger event. The server computing device determines whether a severity level of the trigger event exceeds a threshold severity level, and responsive to determining the severity level of the trigger event exceeds the threshold severity level, replaces on the patient interface the presentation of the virtual avatar with a presentation of a multimedia feed from a computing device of the medical professional.

Abstract: Implantable medical devices include circuitry positioned adjacent to header-related structures, rather than having the header and related structures sitting atop the position of the circuitry within a device housing. A circuit board within the device housing may be positioned adjacently to a lead bore of the header. Feedthrough conductors may extend from the circuitry to conductors of the header while being positioned adjacently to the circuit board. Lead frame conductors may extend to the electrical connectors of the lead bores while also being adjacent to the upper portion of the circuitry. Device height may be reduced by having the circuitry be positioned adjacent to one or more of the various header-related structures.

Abstract: A cardiac pacing system having a pulse generator for generating therapeutic electric pulses, a lead electrically coupled with the pulse generator having an electrode, a first sensor configured to monitor a physiological characteristic of a patient, a second sensor configured to monitor a second physiological characteristic of a patient and a controller. The controller can determine a pacing vector based on variables including a signal received from the second sensor, and cause the pulse generator to deliver the therapeutic electrical pulses according to the determined pacing vector. The controller can also modify pacing characteristics based on variables including a signal received from the second sensor.

Abstract: A tool actuation connector includes a tool activation interface, a longitudinal lock interface and a rotation lock interface. The tool actuation connector includes a latching spring, an inner sleeve and an outer sleeve. The latching spring includes a plurality of spring hooks, for coupling with the tool activation interface. The inner sleeve is operable to longitudinally move relative to the latching spring. The inner sleeve couples the latching spring to the activation interface when the inner sleeve is located over the latching spring and releases the latching spring from the activation interface when the inner sleeve moves away from the latching spring toward the proximal direction. The outer sleeve is rotationally locked with the inner sleeve and is operable to longitudinally move relative to the inner sleeve. The outer sleeve is further operable to rotationally lock with the tool via the rotation lock interface.

Abstract: A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan and a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session. The computer-implemented system may also include a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; write to an associated memory, for access by an artificial intelligence engine, the treatment data; receive, from the artificial intelligence engine, at least one prediction; identify a threshold corresponding to the at least one prediction; and, in response to a determination that the at least one prediction is outside of the range of the threshold, update the treatment data pertaining to the user to indicate the at least one prediction.

Abstract: Computer-implemented systems, computer-implemented methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while the user is performing a treatment plan. The one or more sensors are configured to determine one or more measurements associated with the user. The one or more processing devices are configured to receive, from the one or more sensors while the user performs the treatment plan, the one or more measurements associated with the user. The one or more processing devices also configured to determine, using one or more machine learning models, a probability that the one or more measurements indicate that the user satisfies a threshold for a condition associated with an abnormal heart rhythm.

Abstract: Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.

Abstract: The present invention relates to a system and methods for noninvasively providing therapy for movement disorder symptoms. The present invention provides such a therapy system which provides trans-cranial direct current stimulation (tDCS) in order to treat those symptoms and the disorders. The present invention further provides such tDCS therapy while the subject sleeps in order to minimize the time required and impact of the therapy on the subject's waking life. The system, methods, and devices of the present invention are intended to provide a low-dose electrical current, trans-cranially, to a specific area of the subject's brain while he or she sleeps in order to decrease the occurrence, severity, and duration of the symptoms of movement disorders. The present invention aims to reduce the amount of medication necessary, counteract the effects of medication wearing off during sleep, and to overall improve the quality of life of subjects suffering from movement disorders.

Abstract: A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.

Abstract: A system, apparatus, and method using multiple complementary sensors for the monitoring and wireless communication of several respiration characteristics—that is badge-size, wearable on the outside of clothing, and non-invasive.

Abstract: Neural network based heart rhythm classifiers are described. The neural network is configured to receive an electrocardiogram segment and to output an indication of whether the electrocardiogram segment represents a heart rhythm that is suitable for treatment by a defibrillation shock. Preferably, the received electrocardiogram segment is not transformed or processed prior to its reception by the neural network and no features of the electrocardiogram are identified to the neural network. In some embodiments, the received electrocardiogram segment is the sole input to the neural network. In various embodiments, the neural network is configured to classify electrocardiogram segments obtained while CPR was being performed on the patient. Classifiers that output a characteristic of CPR are also described. Such outputs may include an indication of whether CPR was being performed while the ECG was being detected, compression depth, etc. The described classifiers are well suited for use in defibrillators.

Abstract: Systems and methods for treating a subject with a psychiatric disorder are provided in which a therapy session is conducted. In the therapy session, each respective expression image in a plurality of expression images is sequentially displayed. Each expression image is independently associated with an expression. The successive display of images is construed as a tiled series of expression image subsets, each consisting of N expression images. Upon completion of the display of each respective subset, the user is challenged as to whether the first and the last images in the respective subset exhibit the same emotion. A score is determined for the respective subset based on whether the subject learned to respond correctly. The number of images in each subset is adjusted to a new number based on these scores. A treatment regimen is prescribed to the subject for the psychiatric disorder based at least in part on the scores.