Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more signals from an accelerometer configured in contact with the patient. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.

The purpose of the present invention is to provide a technique whereby multiple projection targets are efficiently identified from multiple neurons in multiple brain areas with the use of multis-point light stimulation. An acquisition unit 52 acquires spike signals generated from multiple neurons existing in the vicinity of two or more recording sites. A stimulation control unit 51 selects one projection target candidate from two or more candidates in accordance with a definite system on the basis of the spike signals and then determines irradiation timing of light stimulation. Upon the light stimulation, a management unit 53 acquires the spike signals in all of the recording sites within a definite period of time before or after the light stimulation, while dividing the spike signals into anti responses and collision responses. An anti response management unit 81 acquires and manages information relating to the anti responses. A collision response management unit 82 acquires and manages information relating to the collision responses. A priority control section 54 corrects and determines priority depending on the anti response information and the collision response information.

Techniques for determining baseline voltages to assess sensed neural responses or other sensed signals in an implantable stimulator device are disclosed, which allows features of the neural responses or other signals to be more easily and reliably established. Features of the neural response, indicative of the AC characteristics of the responses, may be used to control or monitoring stimulation in the device, and certain features may vary with a DC offset voltage in the tissue. The determined baseline voltages compensate for such DC offset voltages, and therefore allow certain AC features of the neural response to be determined more accurately and meaningfully.

A neural recording apparatus including an electrode array including a plurality of electrodes configured to detect voltage signals of one or more neurons and a reference electrode configured to detect a reference signal, a regulator configured to regulate the reference signal, a plurality of transconductance circuits configured to generate current signals by performing transconductance based on the voltage signals and the regulated reference signal, a multiplexer (MUX) configured to multiplex on the generated current signals, and an analog-to-digital converter (ADC) configured to convert the multiplexed current signals into a digital signal

A neural recording apparatus including an electrode array including a plurality of electrodes configured to detect voltage signals of one or more neurons and a reference electrode configured to detect a reference signal, a regulator configured to regulate the reference signal, a plurality of transconductance circuits configured to generate current signals by performing transconductance based on the voltage signals and the regulated reference signal, a multiplexer (MUX) configured to multiplex on the generated current signals, and an analog-to-digital converter (ADC) configured to convert the multiplexed current signals into a digital signal

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.

A system for recording, processing, and monitoring biosignals is provided, the system being configured to suspend data acquisition whenever an electric surgical tool or other generator of high frequency interference is in use. Such a system may protect the hardware of the system and reduce or eliminate the acquisition of distorted signals. The system of some embodiments includes an amplifier system configured to detect the presence of high frequency interference. Related methods are also disclosed.

A system for recording, processing, and monitoring biosignals is provided, the system being configured to suspend data acquisition whenever an electric surgical tool or other generator of high frequency interference is in use. Such a system may protect the hardware of the system and reduce or eliminate the acquisition of distorted signals. The system of some embodiments includes an amplifier system configured to detect the presence of high frequency interference. Related methods are also disclosed.

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 $Z_{\mathrm{IN}}>Z_C\frac{\left(V_{S1}-V_{S2}\right)}{V_E},$
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.

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.