Module for housing electronic and electromechanical medical equipment including a portable digital camera and processing circuitry with machine vision and machine learning software for automatically documenting healthcare events and healthcare equipment operations in the electronic health record.

An infusion safety device comprises a tag reader which is adapted to read a medication tag provided at an infusion medication reservoir, in particular during the whole infusion and a processing unit which is connected with said tag reader and is provided to be connected with an infusion pump in which an infusion protocol is stored and is adapted to recognize a change of the medication reservoir, to read out the infusion protocol from the infusion pump, to cause said tag reader to carry out a reading operation at the latest in case it recognizes a change of the medication reservoir and to give an alarm in case there is no match between the medication read by said tag reader and the medication required by the infusion protocol.

An intravenous drip monitoring method is provided. (A) A monitoring initializing signal is received. (B) A loaded weight is measured to be assigned to be an initial weight and a current weight when the loaded weight is smaller than an empty weight in (C). (D) An alert weight is calculated such that the predetermined minimum alert weight is assigned to be the alert weight. (E) The loaded weight is measured and assigned to be the current weight. (F) When the current weight is not smaller than the alert weight, (E) is performed. (G) When the current weight is between the alert weight and the empty weight, an alert module generates an alert signal and (E) is performed. (H) When the current weight is smaller than the empty weight, a reset to zero and a zero offset calibration is performed on the weighting module and (C) is performed.

A monitoring device provided for monitoring the delivery of fluids through a drip chamber. The device includes an electromagnetic radiation source and a radiation detector. A weight detector is positioned to determine the weight of a fluid reservoir over time, and the detector is positioned with respect to the drip chamber to detect drops falling through the drip chamber. A processor is coupled to the radiation detector and the weight detector to determine flow rate, and is further coupled to a flow restrictor to selectively increase or decrease flow based on the determined flow rate.

An intravenous delivery system may operate by gravity feed, and may have a liquid source containing a liquid, a drip unit that receives the liquid from the liquid source, and tubing that receives the liquid from the drip unit for delivery to a patient. A flow rate sensor may be used to measure a flow rate of liquid through the intravenous delivery system, and may generate a flow rate signal indicative of the flow rate. A controller may receive the signal, and may compare the flow rate with a desired flow rate. If the flow rate is more or less than the desired flow rate, the controller may transmit a control signal to a flow rate regulator. The flow rate regulator may receive the control signal and, in response, modify the flow rate to bring the flow rate closer to the desired flow rate.

An infusion apparatus includes a housing and a chamber configured to be connected to the housing. The apparatus further includes a weight sensor coupled to a load connector connected to the housing and an optical sensor disposed in the housing. The weight sensor is configured to generate a first signal based on a measured weight of the fluid container attached to the housing in a weight-bearing configuration. The optical sensor is configured to generate a second signal based on detecting drops of the fluid traversing the chamber. The apparatus also includes a flow control mechanism to control a flow rate of the fluid into an outlet channel. The apparatus includes one or more processing devices configured to perform operations including transmitting a control signal to the flow control mechanism to adjust the flow rate.

An intravenous delivery system may operate by gravity feed, and may have a liquid source containing a liquid, a drip unit that receives the liquid from the liquid source, and tubing that receives the liquid from the drip unit for delivery to a patient. A flow rate sensor may be used to measure a flow rate of liquid through the intravenous delivery system, and may generate a flow rate signal indicative of the flow rate. A controller may receive the signal, and may compare the flow rate with a desired flow rate. If the flow rate is more or less than the desired flow rate, the controller may transmit a control signal to a flow rate regulator. The flow rate regulator may receive the control signal and, in response, modify the flow rate to bring the flow rate closer to the desired flow rate.

An infusion apparatus includes a housing and a chamber configured to be connected to the housing. The apparatus further includes a weight sensor coupled to a load connector connected to the housing and an optical sensor disposed in the housing. The weight sensor is configured to generate a first signal based on a measured weight of the fluid container attached to the housing in a weight-bearing configuration. The optical sensor is configured to generate a second signal based on detecting drops of the fluid traversing the chamber. The apparatus also includes a flow control mechanism to control a flow rate of the fluid into an outlet channel. The apparatus includes one or more processing devices configured to perform operations including transmitting a control signal to the flow control mechanism to adjust the flow rate.

A de-noising algorithm is executed dynamically as data is received to generate and update a set of candidate solutions. Each candidate solution is a representation of the data using one or more line segments, and each line segment is fitted to the data within the time period that the segment spans. During each iteration of the algorithm, one candidate solution is identified as a best solution, and properties of the best solution are utilized to dynamically compute properties of the data. To limit the number of active candidate solutions and the corresponding processing power required to update and evaluate them, candidate solutions that fall too far behind the best candidate solution are eliminated from consideration. The de-noising algorithm finds particular utility in the context of a load cell signal that is representative of a weight of an intravenous fluid container.

A fluid therapy method for an ADHF patient includes setting a urine output rate desired threshold, setting one or more desired negative net gain rates, and optionally setting a total fluid loss goal. The urine output of the patient is monitored and fluid is automatically administered to the patient at increasing rates to equal to or approximately match the patient's increasing urine output rates until the patient's urine output rate reaches the set urine output rate desired threshold. Thereafter, fluid is administered to the patient at rates to achieve the set desired negative net gain rate until the fluid loss goal is reached. Thereafter, until the end of therapy, fluid is administered to the patient at rates equal to or approximately equal to the monitored urine output rates.