Abstract: Apparatuses, methods, and systems are disclosed for accelerated ergonomic collection of capillary blood. An apparatus and system include a blood collection module with a proximal portion including a vacuum generation chamber, a distal portion including a blood collection chamber, a concave mid portion including a pressure equalization channel configured to equalize reduced air pressure. The apparatus further includes a sealing surface to stably seal the blood collection module to the skin around a collection site and a slide latch actuated by a lengthwise sliding motion. Also included is a lancet carrier with linearly-arranged lancet strips to puncture rows of blood extraction slits in the collection site. The apparatus also includes an angled transfer port with a low-resistance non-microfluidic blood flow channel to a transfer module, then to a plasma separation module with a multilayer laminate and plasma separation membrane. Methods for accelerated ergonomic collection of capillary blood are disclosed.

Abstract: Apparatuses, methods, and systems are disclosed for accelerated ergonomic collection of capillary blood. An apparatus and system include a blood collection module with a proximal portion including a vacuum generation chamber, a distal portion including a blood collection chamber, a concave mid portion including a pressure equalization channel configured to equalize reduced air pressure. The apparatus further includes a sealing surface to stably seal the blood collection module to the skin around a collection site and a slide latch actuated by a lengthwise sliding motion. Also included is a lancet carrier with linearly-arranged lancet strips to puncture rows of blood extraction slits in the collection site. The apparatus also includes an angled transfer port with a low-resistance non-microfluidic blood flow channel to a transfer module, then to a plasma separation module with a multilayer laminate and plasma separation membrane. Methods for accelerated ergonomic collection of capillary blood are disclosed.

Abstract: A system performs intelligent temperature control of equipment, for example, refrigeration equipment, heating equipment, air-conditioning equipment. The system receives signal generated by a sensor mounted in the equipment, for example, a thermistor. The signal monitors an attribute of the equipment, for example, temperature, pressure, or humidity. The system determines an optimal target attribute value for the equipment. The system modifies the signal received from the sensor to generate a modified signal for achieving the optimal target attribute value for the equipment. The system may use a device with variable resistors for generating the modified signal. The system sends the modified signal to a control module of the equipment. The control module controls the equipment to achieve the optimal target attribute value.

Abstract: A system performs intelligent temperature control of equipment, for example, refrigeration equipment, heating equipment, air-conditioning equipment. The system receives signal generated by a sensor mounted in the equipment, for example, a thermistor. The signal monitors an attribute of the equipment, for example, temperature, pressure, or humidity. The system determines an optimal target attribute value for the equipment. The system modifies the signal received from the sensor to generate a modified signal for achieving the optimal target attribute value for the equipment. The system may use a device with variable resistors for generating the modified signal. The system sends the modified signal to a control module of the equipment. The control module controls the equipment to achieve the optimal target attribute value.

Abstract: A system generates alerts based on sensor data obtained from equipment, for example, refrigeration equipment. Examples of equipment instances include refrigeration equipment, heating equipment, air conditioning equipment, and so on. The system accesses a model, for example, a machine learning model trained to predict an alert threshold for generation of alerts. The system modifies the alert threshold value for an equipment instance based on the output of the machine learning model. The system uses the modified alert threshold value for generating alerts. The system may track the number of times the alert threshold was adjusted. If the number of times the alert threshold value is modified exceeds a predetermined fault threshold value, the system determines that the equipment is faulty.

Abstract: A system generates alerts based on sensor data obtained from equipment, for example, refrigeration equipment. Examples of equipment instances include refrigeration equipment, heating equipment, air conditioning equipment, and so on. The system accesses a model, for example, a machine learning model trained to predict an alert threshold for generation of alerts. The system modifies the alert threshold value for an equipment instance based on the output of the machine learning model. The system uses the modified alert threshold value for generating alerts. The system may track the number of times the alert threshold was adjusted. If the number of times the alert threshold value is modified exceeds a predetermined fault threshold value, the system determines that the equipment is faulty.

Abstract: The present invention provides systems, methods, and articles for stress reduction and sleep promotion. A stress reduction and sleep promotion system includes at least one remote device, at least one body sensor, and at least one remote server. In other embodiments, the stress reduction and sleep promotion system includes machine learning.

Abstract: The present invention provides systems, methods, and articles for stress reduction and sleep promotion. A stress reduction and sleep promotion system includes at least one remote device, at least one body sensor, and at least one remote server. In other embodiments, the stress reduction and sleep promotion system includes machine learning.