Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: A wearable computing device may be used to track the efficacy of one or more cleaning actions performed. The device can include one or more sensors that detect and measure motion associated with a cleaning event. In different examples, the movement data generated by the device can be compared to reference movement data to determine if the individual has cleaned all the objects they were expected to clean and/or if the individual has cleaned a given object sufficiently well. As another example, the movement data generated by the device can be analyzed to distinguish cleaning and non-cleaning movement actions as well as to distinguish different types of cleaning actions during cleaning movement. The quality of each cleaning action can be evaluated. In any configuration, the device may perform an operation in response to determining that ineffective cleaning is being performed, causing corrected cleaning action to be performed.

Abstract: Iodine is used in about 80 percent of surgeries in the US to remove some level of microbial load on the skin prior to making an incision. Skin sealants are applied over skin preps to seal the skin and hold any remaining bacteria in place. Iodine produces a characteristic orange-brown color on skin. A skin sealant is provided that has a decolorant that reacts with the iodine found in most skin preps, rendering the skin prep colorless. A skin sealant containing ascorbic acid (vitamin C), Indigo Carmine or Indigo will react with the iodine, thus visually indicating where the skin prep and sealant have been applied and allowing an unobstructed view of the incision.