Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes a motion sensor configured to translate motion of the wearable heart rate monitoring device into a machine-readable motion signal. The wearable heart rate monitoring device also includes a heart rate reporting machine, configured to determine a type of activity currently being performed by the wearer of the wearable heart rate monitoring device based at least in part on the machine-readable motion signal, and output an estimated heart rate based on at least the machine-readable heart rate signal and the type of activity.

Abstract: A method of optical heart rate sensing includes receiving a motion frequency from a motion sensor and receiving an optical signal from an optical sensor. The motion frequency is then filtered from the optical signal, and an estimated heart rate frequency is determined based on the filtered optical signal. A heart rate is reported that is based on the motion frequency, but not based on the estimated heart rate frequency, when a local neighbor magnitude ratio of the estimated heart rate frequency is below a confidence threshold.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes a motion sensor configured to translate motion of the wearable heart rate monitoring device into a machine-readable motion signal. The wearable heart rate monitoring device also includes a heart rate reporting machine, configured to determine a type of activity currently being performed by the wearer of the wearable heart rate monitoring device based at least in part on the machine-readable motion signal, and output an estimated heart rate based on at least the machine-readable heart rate signal and the type of activity.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes an elevation sensor configured to translate an elevation of the wearable heart rate monitoring device into a machine-readable elevation signal. The wearable heart rate monitoring device further includes a heart rate reporting machine configured to output an estimated heart rate based on at least the machine-readable heart rate signal and the machine-readable elevation signal.

Abstract: A system is described for providing the value of a biological characteristic. The system includes a sensor. The sensor is configured to generate a time domain photoplethysmogram (PPG) input signal. The system further includes a first computation module coupled to the sensor. The first computation module is configured to evaluate portions of the generated time domain PPG signal against predetermined quality criteria. The system further includes a second computation module coupled to the first computation module. The second computation module is configured to use portions of the generated time domain PPG signal that meet the predetermined quality criteria to generate an output value. The output value characterizes a biological characteristic at a point in time.

Abstract: Collection and analysis of physiological reading can predict when a person is likely to develop a fever before that person's body temperature increases. In an implementation a device such as a wearable band collects physiological information from its wearer. The physiological information may include heart rate or respiration rate. The person's physiological information classified by an algorithm derived through machine learning techniques. The algorithm may be trained by using data from other individuals who are both healthy and who are sick and/or trained from past reading of the person's own physiological readings. The algorithm may evaluate a value of the person's physiological information to generate probabilities that the person is healthy or that the person likely to become sick and/or develop a fever in the next few days.

Abstract: A method of optical heart rate sensing includes receiving a motion frequency from a motion sensor and receiving an optical signal from an optical sensor. The motion frequency is then filtered from the optical signal, and an estimated heart rate frequency is determined based on the filtered optical signal. A heart rate is reported that is based on the motion frequency, but not based on the estimated heart rate frequency, when a local neighbor magnitude ratio of the estimated heart rate frequency is below a confidence threshold.

Abstract: An optical heart rate sensor stores data indicating the timing of heart beats in a first-in-first-out rolling buffer. During a first condition, new data is added to the rolling buffer and adjusted such that a duration preceding a newly detected heart beat is closer to an average duration between each pair of consecutive heart beats stored in the rolling buffer if the duration preceding the newly detected heart beat differs from the average duration by more than a duration threshold. The rolling buffer is cleared when a number of data adjustments over a predetermined time period exceeds a counting threshold. The rolling buffer is then repopulated such that the duration between each pair of consecutive heart beats is equal to a most recent duration between consecutive heart beats that did not differ from the average duration by more than the duration threshold.

Abstract: A method for an optical heart rate sensor comprises recognizing a minimum amount of motion of the optical heart rate sensor during a testing duration and recognizing an average amount of motion of the optical heart rate sensor during the testing duration. The motion of the optical heart rate sensor is compensated for if the minimum amount of motion during the testing duration exceeds a first threshold, even if the average amount of motion during the testing duration is less than a second threshold, greater than the first threshold. The motion of the optical heart rate sensor is not compensated for if the minimum amount of motion during the testing duration is below the first threshold, even if the average amount of motion during the testing duration is greater than the second threshold.

Abstract: Disclosed are various embodiments of systems and methods for receiving shipment parcels at, for example, materials handling facilities. In some embodiments, a parcel monitoring system detects an exception for a shipment parcel. The parcel monitoring system identifies a vendor associated with the shipment parcel. In response to the exception being detected, the parcel monitoring system controls a conveyor system in accordance with an action specified by an exception handling rule for the vendor.

Abstract: A system and method of extracting formulas in an electronic image of a document using optical character recognition (OCR) is disclosed. In one example, the method comprises analyzing the electronic image, including a plurality of text lines, to generate a plurality of bounding blocks, each bounding block associated with a text line detected within the electronic image, searching the plurality of text lines to detect at least one character matching one of a plurality of character groups, calculating a symbol density of each of the plurality of character groups for each of the plurality of text lines, and classifying each of the plurality of text lines as at least one of an equation block type, an inline equation block type, and a descriptive block type, based on the symbol density, wherein each of the plurality of text lines classified as the equation block type is extracted.

Abstract: Disclosed are various embodiments of systems and methods for receiving shipment parcels at, for example, materials handling facilities. In some embodiments, a parcel monitoring system detects an exception for a shipment parcel. The parcel monitoring system identifies a vendor associated with the shipment parcel. In response to the exception being detected, the parcel monitoring system controls a conveyor system in accordance with an action specified by an exception handling rule for the vendor.

Abstract: Disclosed are various embodiments of systems and methods for receiving shipment parcels at materials handling facilities. A parcel receiving system has an imaging tunnel through which shipment parcels received at a materials handling facility are passed. While a shipment parcel is passing through the imaging tunnel, a camera captures at least one image of the parcel. The parcel image is electronically analyzed to discover various tracking information and to detect various types of exceptions, such as damage to the parcel or defective tracking information. In addition, the captured image is stored in order to create a visual record of the parcel at the time of reception. This record may be used in a variety of ways, such as resolving or tracking exceptions or providing feedback to the vendor or shipment carrier. In addition, the parcel image may be viewed by a user to enable the user to detect and/or resolve an exception.

Abstract: Disclosed are various embodiments of systems and methods for receiving shipment parcels at materials handling facilities. A parcel receiving system has an imaging tunnel through which shipment parcels received at a materials handling facility are passed. While a shipment parcel is passing through the imaging tunnel, a camera captures at least one image of the parcel. The parcel image is electronically analyzed to discover various tracking information and to detect various types of exceptions, such as damage to the parcel or defective tracking information. In addition, the captured image is stored in order to create a visual record of the parcel at the time of reception. This record may be used in a variety of ways, such as resolving or tracking exceptions or providing feedback to the vendor or shipment carrier. In addition, the parcel image may be viewed by a user to enable the user to detect and/or resolve an exception.