A sensing electrode selection algorithm is disclosed for use with an implantable pulse generator having an electrode array. The algorithm automatically selects optimal sensing electrodes in the array to be used with a pre-determined stimulation therapy appropriate for the patient. The algorithm preferably senses stimulation artifacts using different sensing electrodes, and more specifically different sensing electrode pairs as is appropriate when differential sensing is used. The algorithm further preferably senses these stimulation artifacts with the patient placed in two or more postures. The algorithm processes the stimulation artifact features measured at the different sensing electrodes and at the different postures to automatically determine one or more sensing electrode pairs that best distinguishes the two or more postures given the prescribed stimulation therapy.

A sensing electrode selection algorithm is disclosed for use with an implantable pulse generator having an electrode array. The algorithm automatically selects optimal sensing electrodes in the array to be used with a pre-determined stimulation therapy appropriate for the patient. The algorithm preferably senses stimulation artifacts using different sensing electrodes, and more specifically different sensing electrode pairs as is appropriate when differential sensing is used. The algorithm further preferably senses these stimulation artifacts with the patient placed in two or more postures. The algorithm processes the stimulation artifact features measured at the different sensing electrodes and at the different postures to automatically determine one or more sensing electrode pairs that best distinguishes the two or more postures given the prescribed stimulation therapy.

A sensing electrode selection algorithm is disclosed for use with an implantable pulse generator having an electrode array. The algorithm automatically selects optimal sensing electrodes in the array to be used with a pre-determined stimulation therapy appropriate for the patient. The algorithm preferably senses stimulation artifacts using different sensing electrodes, and more specifically different sensing electrode pairs as is appropriate when differential sensing is used. The algorithm further preferably senses these stimulation artifacts with the patient placed in two or more postures. The algorithm processes the stimulation artifact features measured at the different sensing electrodes and at the different postures to automatically determine one or more sensing electrode pairs that best distinguishes the two or more postures given the prescribed stimulation therapy.

Disclosed is an assisted programming system for a neuromodulation device that is configured to assist a clinician to efficiently program the neuromodulation device for a particular patient. In particular, the assisted programming system comprises a user interface with a plurality of controls such as switches, each switch control corresponding to a predetermined configuration of the stimulus electrodes. Activation and de-activation of the switch controls causes stimuli to be delivered via the respective stimulus electrode configurations. Alternatively, or additionally, the user interface controls may be tiles, whose activation may cause the state of delivery of stimulation via the respective stimulus electrode configurations to be inverted.

A system for detecting strokes includes a sensor device configured to obtain physiological data from a patient, for example brain activity data. The sensor device can include electrodes configured to be disposed at the back of the patient's neck or base of the skull. The electrodes can detect electrical signals corresponding to brain activity in the P3, Pz, and/or P4 brain regions or other brain regions. A computing device communicatively coupled to the sensor device is configured to receive the physiological data and analyze it to indicate whether the patient has suffered a stroke.

A method for assessing peripheral nerve stimulation (PNS) for a coil geometry includes retrieving a PNS Huygens' P-matrix for a body model. The PNS Huygens' P-matrix is defined on a Huygens' surface enclosing the body model. The method further includes generating a coil specific PNS P-matrix for the coil geometry based on at least the PNS Huygens' P-matrix for the body model, determining at least one PNS threshold for the coil geometry based on the coil specific PNS P-matrix, and storing the at least one PNS threshold in a storage device.

A method for assessing peripheral nerve stimulation (PNS) for a coil geometry includes retrieving a PNS Huygens' P-matrix for a body model. The PNS Huygens' P-matrix is defined on a Huygens' surface enclosing the body model. The method further includes generating a coil specific PNS P-matrix for the coil geometry based on at least the PNS Huygens' P-matrix for the body model, determining at least one PNS threshold for the coil geometry based on the coil specific PNS P-matrix, and storing the at least one PNS threshold in a storage device.

Measuring a neural response to a stimulus comprises applying an electrical stimulus, then imposing a delay during which the stimulus electrodes are open circuited. During the delay, a neural response signal present at sense electrodes is measured with a measurement amplifier, while ensuring that an impedance between the sense electrodes is sufficiently large that a voltage arising on the sense electrode tissue interface in response to the stimulus is constrained to a level which permits assessment of the neural response voltage seen at the sense electrode. For example the input impedance to the measurement amplifier (Z.sub.IN) can be

[00001]$Z_{\mathrm{IN}}>Z_C.Math.\frac{\left(V_{S.Math..Math.1}-V_{S.Math..Math.2}\right)}{V_E},$

where Z.sub.C is the sense electrode(s) constant phase element impedance, V.sub.s1V.sub.s2 is the differential voltage arising on the sense electrode tissue interface, and V.sub.E is the neural response voltage seen at the sense electrode.

Systems and methods for gesture control are described. In some embodiments, a system for assessing a physiological state of a user. The system may include the wearable device comprising one or more electrodes configured to be disposed adjacent to an external surface of the skin portion. A first timestamp may be determined. The first timestamp may indicate a first time at which a stimulus is presented to the user. A second timestamp indicating a second time at which the biopotential signals indicate an intention by the user to perform a responsive action may be determined. Based at least on the first timestamp and the second timestamp, determine a subject response time for the user. The subject response time may be compared to a baseline response time for the user to generate an assessment of a physiological state of the user.

Systems and methods for gesture control are described. In some embodiments, a system for assessing a physiological state of a user. The system may include the wearable device comprising one or more electrodes configured to be disposed adjacent to an external surface of the skin portion. A first timestamp may be determined. The first timestamp may indicate a first time at which a stimulus is presented to the user. A second timestamp indicating a second time at which the biopotential signals indicate an intention by the user to perform a responsive action may be determined. Based at least on the first timestamp and the second timestamp, determine a subject response time for the user. The subject response time may be compared to a baseline response time for the user to generate an assessment of a physiological state of the user.