Methods, systems, and media are disclosed for reconstructing bioelectronic lead placement. In some embodiments, the disclosed system can include a processor configured to determine relationships between EP signals of one or more pairs of a plurality of electrodes over one or more sampling time periods, wherein the plurality electrodes are separately placed on a patient's body for collecting the EP signals, and to reconstruct geometry of the plurality of electrodes based on the relationships between the EP signals.

An implantable neurostimulator (INS) and method of use, the INS including an electrical lead having formed thereon at least a pair of bi-polar electrodes, wherein the electrical lead is configured for placement of the pair of bi-polar electrodes proximate protrusor muscles of a patient, a pulse generator electrically connected to the electrical lead and configured to deliver electrical energy to the pair of bi-polar electrodes, the pulse generator having mounted therein a sensor and a control circuit, and the sensor is configured to generate signals representative of an orientation of the pulse generator and communicate the signals to the control circuit and the control circuit is configured to determine the orientation of the pulse generator and deliver electrical energy to the bi-polar electrodes when the determined orientation correlates to a pre-determined orientation.

The purpose of the present invention is to provide a biological information measurement garment having excellent peel strength between a clothing fabric including spun yarns and an electrode. The garment includes a clothing fabric; and an electrode formed on a skin-side surface of the clothing fabric, the clothing fabric including spun yarns present on the skin-side surface on which the electrode is formed, and each of the spun yarns satisfying a following formula (1):

F/(0.8673/√Ne)<4500  (1), wherein F represents a number of fluffy fibers (fibers/10 m) having a length of 1 mm or more, per 10 m of the spun yarn, and Ne represents an English yarn count of the spun yarn.

An apparatus having a ring-shaped housing configured to be wrapped round a finger of a user, the ring-shaped housing having an opening or a joint at a first point round the finger and a first contiguous section that is at a location opposite to the first point across a central axis of the ring-shaped housing; an antenna configured in the ring-shaped housing in the contiguous section; an inertial measurement unit configured to measure motions of the finger; a light-emitting diode (LED) indicator configured on an outer portion of the ring-shaped housing; a charging pad configured to charge a battery configured in the ring-shaped housing; and/or a touch pad configured to receive touch input from a finger of the user.

An electrode for measuring bioelectric signals of an individual includes a dome-like shape support body having a concave contact side facing the individual and an opposite convex connector side. The support body defines a central axis arranged centrally through the contact and connector sides. The electrode includes outer contact pins located on the contact side at a radially outer region of the support body for contacting an area of interest to be measured. The electrode is made of elastomeric material and has conductive properties. The support body is flexible such that after applying the electrode to the individual a force exerted centrally onto the connector side and parallel to the central axis leads to an upwards bending of the radially outer region. The upwards bending leads to tilting of the outer contact pins such that a tip of the outer contact pins moves radially outwards along the area of interest.

A multimodal data acquisition and communication system and method for distributed management of transdiagnostic behavioral therapy (TBT). An exemplary system, method, and apparatus according to certain aspects of the present disclosure may include a patient interface comprising (a) one or more sensors configured to collect quantitative (e.g., physiological data) and qualitative data (e.g., video/audio data) from a patient user during a TBT session, and (b) a mobile computing device, such as a smartphone, comprising a mobile software application configured to establish a data transfer interface with the one or more sensors and provide a graphical user interface to the patient user. The mobile computing device may be communicatively engaged with a cloud-based server over a wireless communications network to enable real-time collection, communication, storage and analysis of TBT data and bi-directional audio/video communication with at least one clinician client device.

Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and generating an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and generating an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

A method, a computer program and a breathing apparatus relates to determination of at least one physiological parameter including the neuromechanical efficiency [NME] of a patient being mechanically ventilated by the breathing apparatus. This is achieved by obtaining samples of an airway pressure (P.sub.aw), a patient flow (Ø), a change in lung volume (V) caused by the patient flow, and an electrical activity of a respiratory muscle of the patient, during ventilation of the patient at a first level of ventilatory assist and a second and different level of ventilatory assist, and determining the at least one physiological parameter, including NME, from the airway pressure samples, the patient flow samples, the samples of the change in lung volume, and the samples of the electrical activity of the respiratory muscle, obtained at the different levels of ventilatory assist.

A method, a computer program and a breathing apparatus relates to determination of at least one physiological parameter including the neuromechanical efficiency [NME] of a patient being mechanically ventilated by the breathing apparatus. This is achieved by obtaining samples of an airway pressure (P.sub.aw), a patient flow (Ø), a change in lung volume (V) caused by the patient flow, and an electrical activity of a respiratory muscle of the patient, during ventilation of the patient at a first level of ventilatory assist and a second and different level of ventilatory assist, and determining the at least one physiological parameter, including NME, from the airway pressure samples, the patient flow samples, the samples of the change in lung volume, and the samples of the electrical activity of the respiratory muscle, obtained at the different levels of ventilatory assist.