A sensor interface system for providing a connection between at least one sensor and a maternal-fetal monitor, wherein the interface system converts electrical muscle activity captured by the sensor(s) into uterine activity data signals for use by the maternal-fetal monitor. The sensor interface system of the invention preferably includes a conversion means for converting the signals from the sensor(s) into signals similar to those produced by a tocodynamometer.

A method of calculating in vivo force on an anterior cruciate ligament (ACL) by measuring one or more biomechanical properties during a biomechanical screening task to obtain one or more biomechanical datum from the measured one or more biomechanical properties, and calculating a total load on an anterior cruciate ligament from an ACL force model using the one or more biomechanical datum as inputs to the ACL force model. The ACL force model is defined by F.sub.ACL=F.sub.ACL.sup.sag+F.sub.ACL.sup.front+F.sub.ACL.sup.trans+Σ.sub.jCT.sub.j, wherein F.sub.ACL is the total force on the ACL, F.sub.ACL.sup.sag is the force on the ACL in a sagittal plane, F.sub.ACL.sup.front is the force on the ACL in the frontal plane, F.sub.ACL.sup.trans is the force on the ACL in the transverse plane, and CT.sub.j is the ACL force interaction relationships among the sagittal-frontal (SF), sagittal-transverse (ST), and frontal-transverse (FT) planes, where j=SF, ST, FT.

A method of calculating in vivo force on an anterior cruciate ligament (ACL) by measuring one or more biomechanical properties during a biomechanical screening task to obtain one or more biomechanical datum from the measured one or more biomechanical properties, and calculating a total load on an anterior cruciate ligament from an ACL force model using the one or more biomechanical datum as inputs to the ACL force model. The ACL force model is defined by F.sub.ACL=F.sub.ACL.sup.sag+F.sub.ACL.sup.front+F.sub.ACL.sup.trans+Σ.sub.jCT.sub.j, wherein F.sub.ACL is the total force on the ACL, F.sub.ACL.sup.sag is the force on the ACL in a sagittal plane, F.sub.ACL.sup.front is the force on the ACL in the frontal plane, F.sub.ACL.sup.trans is the force on the ACL in the transverse plane, and CT.sub.j is the ACL force interaction relationships among the sagittal-frontal (SF), sagittal-transverse (ST), and frontal-transverse (FT) planes, where j=SF, ST, FT.

System and methods are disclosed that promote a sleep stage of a user. The systems and methods determine a current sleep stage of a user during a sleep session, with the user using a respiratory therapy system during the sleep session. The systems and methods further predict an undesired sleep stage upcoming for the user during the sleep session based, at least in part, on (i) one or more user parameters, information from one or more previous sleep sessions, or a combination thereof, and (ii) the current sleep stage. The systems and methods adjust one or more control parameters of the respiratory therapy system, of one or more devices in an environment of the user, or of a combination thereof to promote a desired sleep stage of the user, thereby optimizing sleep of the user.

A device includes a sensor signal input node and a high-pass filter stage. The high-pass filter stage includes an operational amplifier and a feedback integrator. The operational amplifier includes an input node coupled to the sensor signal input node. The feedback integrator is coupled between an output node of the operational amplifier and the input node of the operational amplifier to set a high-pass pole frequency of the high-pass filter stage.

A system for non-invasively acquiring maternal and/or fetal biopotential signals includes a wearable device configured to be worn by a pregnant patient comprising a plurality of electrodes configured to detect maternal and/or fetal biopotential signals associated with the patient and her fetus. The system further includes a computing device configured to receive the maternal and/or fetal biopotential signals from each of a plurality of electrode pairs and select, based on processing the maternal and/or fetal biopotential signals, one of the plurality of electrodes to use as a reference electrode during a monitoring session for the patient.

An example device includes memory configured to store a measure of COPD severity of a patient and processing circuitry communicatively coupled to the memory. The processing circuitry is configured to receive an electromyogram (EMG) of the patient, receive one or more signals indicative of respiration rate of the patient, and receive one or more signals indicative of tidal volume of the patient. The processing circuitry is configured to determine, based on the respiration rate of the patient and the tidal volume of the patient, a minute ventilation of the patient. The processing circuitry is configured to determine, based on the minute ventilation of the patient and the EMG of the patient, the measure of COPD severity of the patient, and generate an indication for output that is based at least in part on the measure of COPD severity of the patient.

An example device includes memory configured to store a measure of COPD severity of a patient and processing circuitry communicatively coupled to the memory. The processing circuitry is configured to receive an electromyogram (EMG) of the patient, receive one or more signals indicative of respiration rate of the patient, and receive one or more signals indicative of tidal volume of the patient. The processing circuitry is configured to determine, based on the respiration rate of the patient and the tidal volume of the patient, a minute ventilation of the patient. The processing circuitry is configured to determine, based on the minute ventilation of the patient and the EMG of the patient, the measure of COPD severity of the patient, and generate an indication for output that is based at least in part on the measure of COPD severity of the patient.

The technology disclosed can be implemented to construct devices with an array of optical elements to provide power to stimulate a biological process in a nerve system in living objects, and to provide patterned light outputs from the array of optical elements to indicate a corresponding electrical pattern monitored from the biological process in the nerve system. In one aspect a nerve stimulator apparatus is disclosed including a plurality of optical to electrical transducers arranged in a two-dimensional array, wherein each of the plurality of optical to electrical transducers is configured to convert light to an electrical signal; a plurality of electrodes, each electrode associated with one or more associated optical to electrical transducers; and a plurality of electrical interconnects to connect each of the plurality of electrodes to the one or more associated optical transducers. In another aspect nerve sensor apparatus is disclosed including a plurality of optical to electrical transducers; a plurality of optical sources; a plurality of electrodes, each electrode associated with one or more optical to electrical transducers, each optical source configured to modulate light output according to a voltage at one of the plurality of electrodes; and a plurality of electrical interconnects.

This disclosure relates generally to a method and system that provides personalized neuro motor rehabilitation therapy using a musculoskeletal arm model. The arm model is personalized using anthropometric measures and further adapted to operate using an optimized set of muscle actuators considering associated redundancy. The method generates trajectories associated with reach motion profiles for each motion task utilizing joint kinematics and inverse dynamics by integrating forward dynamics and muscle synergy concepts to select the optimized set of muscle actuators. The generated trajectories are further ranked based on muscle synergy, minimum energy consumption and optimized trajectory to select rehabilitation therapy best suited for effective recovery. Conventional methods that work with neural dynamics in deriving muscle synergy are dependent on single tasks, leaving synergy variation with task variability unexplored. The present disclosure provides understanding of work space, task variability and synergy paradigm to derive conclusive control actions for aiding rehabilitation effectively.