Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes at least a processor and a memory communicatively connected to at least a processor. A memory contains instructions configuring at least a processor to receive optical data from a sensor in electronic communication with the at least a processor. At least a processor is configured to determine a procedural performance parameter as a function of optical data. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes a processor and a memory communicatively connected to at least a processor. The memory contains instructions configuring at least a processor to receive optical data from a sensor, wherein a machine vision system is configured to identify at least one object within optical data. At least a processor is configured to determine a procedural performance parameter as a function of optical data wherein determining the procedural performance parameter comprises classifying the at least one object within optical data to an optical data category using an optical data classifier. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: Described herein is a system and a method for collaborative training of a machine learning model for pose estimation. The system includes a remote computing device in communication with a local computing device, wherein the remote computing device is configured to instruct the local computing device to receive a first image; and generate a first pose datum as a function of the first image using a local machine learning model. The remote computing device is configured to receive, from the local computing device, the first pose datum; generate a second pose datum as a function of the first pose datum and the first image using a remote machine learning model; and configure the local computing device to retrain the local machine learning model as a function of the second pose datum.

Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes at least a processor and a memory communicatively connected to at least a processor. A memory contains instructions configuring at least a processor to receive optical data from a sensor in electronic communication with the at least a processor. At least a processor is configured to determine a procedural performance parameter as a function of optical data. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes at least a processor and a memory communicatively connected to at least a processor. A memory contains instructions configuring at least a processor to receive optical data from a sensor comprising a machine vision system in electronic communication with the at least a processor, wherein the machine vision system is configured to identify at least one object within optical data. At least a processor is configured to determine a procedural performance parameter as a function of optical data wherein determining the procedural performance parameter comprises classifying the at least one object within optical data to an optical data category using an optical data classifier. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes at least a processor and a memory communicatively connected to at least a processor. A memory contains instructions configuring at least a processor to receive optical data from a sensor in electronic communication with the at least a processor. At least a processor is configured to determine a procedural performance parameter as a function of optical data. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: In an aspect, an apparatus for procedural training is presented. An apparatus includes at least a processor and a memory communicatively connected to at least a processor. A memory contains instructions configuring at least a processor to receive optical data from a sensor in electronic communication with the at least a processor. At least a processor is configured to determine a procedural performance parameter as a function of optical data. At least a processor is configured to compare a procedural performance parameter to a procedural performance threshold. At least a processor is configured to display procedural training feedback through a display unit as a function of a comparison.

Abstract: A mannequin (200) including a chest compression feedback mechanism for use in simulated cardiopulmonary resuscitation (CPR) training includes a box (203) for simulating a human chest such that a head (201) is connected to one side of the box (203). A mechanical noise generator (215) is positioned within the box (203) for making an audible sound when force is applied to a predetermined area of the box during simulated chest compressions. This sound indicates to the teacher and/or student that a required compression depth has been met during CPR training.