Abstract:
By combining data from different sensors (on fitness device, mobile smartphone, smart clothing, other devices or people in same location), an intelligent system provides a better indicator of an individual&#39;s physical effort, using rich data sources to enhance quantified metrics such as distance/pace/altitude gain, to provide a clearer picture of an individual&#39;s exercise and activity.

Description:
[0001]    This application claims priority to U.S. provisional patent application Ser. No. 61/878,835, filed Sep. 17, 2013. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The present application relates generally to digital ecosystems that are configured for use when engaging in physical activity and/or fitness exercises. 
       BACKGROUND OF THE INVENTION 
       [0003]    Society is becoming increasingly health-conscious. A wide variety of exercise and workouts are now offered to encourage people to stay fit through exercise. As understood herein, while stationary exercise equipment often comes equipped with, data displays for the information of the exerciser, the information is not tailored to the individual and is frequently repetitive and monotonous. As further understood herein, people enjoy listening to music as workout aids but the music typically is whatever is broadcast within a gymnasium or provided on a recording device the user may wear, again being potentially monotonous and unchanging in pattern and beat in a way that is uncoupled from the actual exercise being engaged in. Furthermore, general fitness devices that monitor physical exertion during exercise do not always seem to provide an accurate enough picture of true effort. 
       SUMMARY OF THE INVENTION 
       [0004]    Present principles recognize that by combining data from different sensors (on fitness device, mobile smartphone, smart clothing, other devices/people in same location/time), a monitoring system can provide a better indicator of true effort. This might not necessarily be a quantified “calories” or “distance”, but a way to factor in ‘difficulty’ to help provide more nuance and qualification to a quantified measurement. 
         [0005]    Accordingly, a device includes a computer readable storage medium bearing instructions executable by a processor, and a processor configured for accessing the computer readable storage medium to execute the instructions to configure the processor for receiving signals from a position sensor from which the processor can calculate a speed and a distance over an interval of time ΔT. The processor is configured for receiving a signal representing a weather condition, and another signal representing a biometric condition of a user of the device. The processor then adjusts a baseline value associated with the speed and/or distance based on the biometric condition and weather condition to render an adjusted baseline, and outputs an indicia of exercise effort based on the adjusted baseline. 
         [0006]    In some embodiments, the processor when executing the instructions is further configured for receiving a signal representing a slope of terrain associated with the exercise effort, and adjusting the baseline value based on the slope. The processor also may receive a signal representing an elevation and/or type of terrain associated with the exercise effort, and adjust the baseline value based on the elevation and/or type. 
         [0007]    The weather condition can include one or more of humidity, temperature, barometric pressure, and wind condition. The biometric condition can include one or more of heart rate, leg stride condition, sleep condition, and skin temperature. 
         [0008]    In another aspect, a method includes establishing a baseline effort indicator at least partially based on a pace and distance of an exercise of a person. The baseline effort indicator is adjusted based on a biometric condition of the person, a weather condition, and a terrain condition, and an adjusted effort indicator is output based at least in part on the adjusting steps. 
         [0009]    In another aspect, a device includes a computer readable storage medium bearing instructions executable by a processor, and a processor configured for accessing the computer readable storage medium to execute the instructions to configure the processor for combining data from at least one biometric sensor and one or more of weather information and terrain information. This provides an indication of an individual&#39;s physical effort during an exercise to enhance quantified metrics and provide an accurate picture of an individual&#39;s exercise and activity. 
         [0010]    The details of the present invention, both as to its structure and operation, can best be understood in reference to the accompanying drawings, in which like reference numerals refer to like parts, and in which: 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]      FIG. 1  is a block diagram of an example system including an example in accordance with present principles; 
           [0012]      FIG. 2  is a block diagram of an example specific system; 
           [0013]      FIG. 3  is a flowchart of example logic; and 
           [0014]      FIG. 4  is a schematic diagram illustrating present principles. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0015]    This disclosure relates generally to consumer electronics (CE) device based user information. A system herein may include server and client components, connected over a network such that data may be exchanged between the client and server components. The client components may include one or more computing devices including portable televisions (e.g. smart TVs, Internet-enabled TVs), portable computers such as laptops and tablet computers, and other mobile devices including smart phones and additional examples discussed below. These client devices may operate with a variety of operating environments. For example, some of the client computers may employ, as examples, operating systems from Microsoft, or a Unix operating system, or operating systems produced by Apple Computer or Google. These operating environments may be used to execute one or more browsing programs, such as a browser made by Microsoft or Google or Mozilla or other browser program that can access web applications hosted by the Internet servers discussed below. 
         [0016]    Servers may include one or more processors executing instructions that configure the servers to receive and transmit data over a network such as the Internet. Or, a client and server can be connected over a local intranet or a virtual private network. 
         [0017]    Information may be exchanged over a network between the clients and servers. To this end and for security, servers and/or clients can include firewalls, load balancers, temporary storages, and proxies, and other network infrastructure for reliability and security. One or more servers may form an apparatus that implement methods of providing a secure community such as an online social website to network members. 
         [0018]    As used herein, instructions refer to computer-implemented steps for processing information in the system. Instructions can be implemented in software, firmware or hardware and include any type of programmed step undertaken by components of the system. 
         [0019]    A processor may be any conventional general purpose single- or multi-chip processor that can execute logic by means of various lines such as address lines, data lines, and control lines and registers and shift registers. 
         [0020]    Software modules described by way of the flow charts and user interfaces herein can include various sub-routines, procedures, etc. Without limiting the disclosure, logic stated to be executed by a particular module can be redistributed to other software modules and/or combined together in a single module and/or made available in a shareable library. 
         [0021]    Present principles described herein can be implemented as hardware, software, firmware, or combinations thereof; hence, illustrative components, blocks, modules, circuits, and steps are set forth in terms of their functionality. 
         [0022]    Further to what has been alluded to above, logical blocks, modules, and circuits described below can be implemented or performed with a general purpose processor, a digital signal processor (DSP), a field programmable gate array (FPGA) or other programmable logic device such as an application specific integrated circuit (ASIC), discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A processor can be implemented by a controller or state machine or a combination of computing devices. 
         [0023]    The functions and methods described below, when implemented in software, can be written in an appropriate language such as but not limited to C# or C++, and can be stored on or transmitted through a computer-readable storage medium such as a random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), compact disk read-only memory (CD-ROM) or other optical disk storage such as digital versatile disc (DVD), magnetic disk storage or other magnetic storage devices including removable thumb drives, etc. A connection may establish a computer-readable medium. Such connections can include, as examples, hard-wired cables including fiber optics and coaxial wires and digital subscriber line (DSL) and twisted pair wires. Such connections may include wireless communication connections including infrared and radio. 
         [0024]    Components included in one embodiment can be used in other embodiments in any appropriate combination. For example, any of the various components described herein and/or depicted in the Figures may be combined, interchanged or excluded from other embodiments. 
         [0025]    “A system having at least one of A, B, and C” (likewise “a system having at least one of A, B, or C” and “a system having at least one of A, B, C”) includes systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc. 
         [0026]    Before describing  FIG. 1 , it is to be understood that the CE devices and software described herein are understood to be usable in the context of a digital ecosystem. Thus, as understood herein, a computer ecosystem, or digital ecosystem, may be an adaptive and distributed socio-technical system that is characterized by its sustainability, self-organization, and scalability. Inspired by environmental ecosystems, which consist of biotic and abiotic components that interact through nutrient cycles and energy flows, complete computer ecosystems consist of hardware, software, and services that in some cases may be provided by one company, such as Sony Electronics. The goal of each computer ecosystem is to provide consumers with everything that may be desired, at least in part services and/or software that may be exchanged via the Internet. Moreover, interconnectedness and sharing among elements of an ecosystem, such as applications within a computing cloud, provides consumers with increased capability to organize and access data and presents itself as the future characteristic of efficient integrative ecosystems. 
         [0027]    Two general types of computer ecosystems exist: vertical and horizontal computer ecosystems. In the vertical approach, virtually all aspects of the ecosystem are associated with the same company (e.g. produced by the same manufacturer), and are specifically designed to seamlessly interact with one another. Horizontal ecosystems, one the other hand, integrate aspects such as hardware and software that are created by differing entities into one unified ecosystem. The horizontal approach allows for greater variety of input from consumers and manufactures, increasing the capacity for novel innovations and adaptations to changing demands. But regardless, it is to be understood that some digital ecosystems, including those referenced herein, may embody characteristics of both the horizontal and vertical ecosystems described above. 
         [0028]    Accordingly, it is to be further understood that these ecosystems may be used while engaged in physical activity to e.g. provide inspiration, goal fulfillment and/or achievement, automated coaching/training, health and exercise analysis, convenient access to data, group sharing (e.g. of fitness data), and increased accuracy of health monitoring, all while doing so in a stylish and entertaining manner. Further still, the devices disclosed herein are understood to be capable of making diagnostic determinations based on data from various sensors (such as those described below in reference to  FIG. 1 ) for use while exercising, for exercise monitoring (e.g. in real time), and/or for sharing of data with friends (e.g. using a social networking service) even when not all people have the same types and combinations of sensors on their respective CE devices. 
         [0029]    Thus, it is to be understood that the CE devices described herein may allow for easy and simplified user interaction with the device so as to not be unduly bothersome or encumbering e.g. before, during, and after an exercise. 
         [0030]    Now specifically referring to  FIG. 1 , an example system  10  is shown, which may include one or more of the example devices mentioned above and described further below to enhance fitness experiences in accordance with present principles. The first of the example devices included in the system  10  is an example consumer electronics (CE) device  12  that may be waterproof (e.g., for use while swimming). The CE device  12  may be, e.g., a computerized Internet enabled (“smart”) telephone, a tablet computer, a notebook computer, a wearable computerized device such as e.g. computerized Internet-enabled watch, a computerized Internet-enabled bracelet, other computerized Internet-enabled fitness devices, a computerized Internet-enabled music player, computerized Internet-enabled head phones, a computerized Internet-enabled implantable device such as an implantable skin device, etc., and even e.g. a computerized Internet-enabled television (TV). Regardless, it is to be understood that the CE device  12  is configured to undertake present principles (e.g. communicate with other CE devices to undertake present principles, execute the logic described herein, and perform any other functions and/or operations described herein). 
         [0031]    Accordingly, to undertake such principles the CE device  12  can include some or all of the components shown in  FIG. 1 . For example, the CE device  12  can include one or more touch-enabled displays  14 , one or more speakers  16  for outputting audio in accordance with present principles, and at least one additional input device  18  such as e.g. an audio receiver/microphone for e.g. entering audible commands to the CE device  12  to control the CE device  12 . The example CE device  12  may also include one or more network interfaces  20  for communication over at least one network  22  such as the Internet, an WAN, an LAN, etc. under control of one or more processors  24 . It is to be understood that the processor  24  controls the CE device  12  to undertake present principles, including the other elements of the CE device  12  described herein such as e.g. controlling the display  14  to present images thereon and receiving input therefrom. Furthermore, note the network interface  20  may be, e.g., a wired or wireless modem, or router, or other appropriate interface such as, e.g., a wireless telephony transceiver, WiFi transceiver, etc. 
         [0032]    In addition to the foregoing, the CE device  12  may also include one or more input ports  26  such as, e.g., a USB port to physically connect (e.g. using a wired connection) to another CE device and/or a headphone port to connect headphones to the CE device  12  for presentation of audio from the CE device  12  to a user through the headphones. The CE device  12  may further include one or more tangible computer readable storage medium  28  such as disk-based or solid state storage, it being understood that the computer readable storage medium  28  may not be a carrier wave. Also in some embodiments, the CE device  12  can include a position or location receiver such as but not limited to a GPS receiver and/or altimeter  30  that is configured to e.g. receive geographic position information from at least one satellite and provide the information to the processor  24  and/or determine an altitude at which the CE device  12  is disposed in conjunction with the processor  24 . However, it is to be understood that that another suitable position receiver other than a GPS receiver and/or altimeter may be used in accordance with present principles to e.g. determine the location of the CE device  12  in e.g. all three dimensions. 
         [0033]    Continuing the description of the CE device  12 , in some embodiments the CE device  12  may include one or more cameras  32  that may be, e.g., a thermal imaging camera, a digital camera such as a webcam, and/or a camera integrated into the CE device  12  and controllable by the processor  24  to gather pictures/images and/or video in accordance with present principles (e.g. to share aspects of a physical activity such as hiking with social networking friends). Also included on the CE device  12  may be a Bluetooth transceiver  34  and other Near Field Communication (NFC) element  36  for communication with other devices using Bluetooth and/or NFC technology, respectively. An example NFC element can be a radio frequency identification (RFID) element. 
         [0034]    Further still, the CE device  12  may include one or more motion sensors  37  (e.g., an accelerometer, gyroscope, cyclometer, magnetic sensor, infrared (IR) motion sensors such as passive IR sensors, an optical sensor, a speed and/or cadence sensor, a gesture sensor (e.g. for sensing gesture command), etc.) providing input to the processor  24 . The CE device  12  may include still other sensors such as e.g. one or more climate sensors  38  (e.g. barometers, humidity sensors, wind sensors, light sensors, temperature sensors, etc.) and/or one or more biometric sensors  40  (e.g. heart rate sensors and/or heart monitors, calorie counters, blood pressure sensors, perspiration sensors, odor and/or scent detectors, fingerprint sensors, facial recognition sensors, iris and/or retina detectors, DNA sensors, oxygen sensors (e.g. blood oxygen sensors and/or VO2 max sensors), glucose and/or blood sugar sensors, sleep sensors (e.g. a sleep tracker), pedometers and/or speed sensors, body temperature sensors, nutrient and metabolic rate sensors, voice sensors, lung input/output and other cardiovascular sensors, etc.) also providing input to the processor  24 . In addition to the foregoing, it is noted that in some embodiments the CE device  12  may also include a kinetic energy harvester  42  to e.g. charge a battery (not shown) powering the CE device  12 . 
         [0035]    Still referring to  FIG. 1 , in addition to the CE device  12 , the system  10  may include one or more other CE device types such as, but not limited to, a computerized Internet-enabled bracelet  44 , computerized Internet-enabled headphones and/or ear buds  46 , computerized Internet-enabled clothing  48 , a computerized Internet-enabled exercise machine  50  (e.g. a treadmill, exercise bike, elliptical machine, etc.), etc. Also shown is a computerized Internet-enabled gymnasium entry kiosk  52  permitting authorized entry to a gymnasium housing the exercise machine  50 . It is to be understood that other CE devices included in the system  10  including those described in this paragraph may respectively include some or all of the various components described above in reference to the CE device  12  such but not limited to e.g. the biometric sensors and motion sensors described above, as well as the position receivers, cameras, input devices, and speakers also described above. 
         [0036]    Thus, for instance, the headphones/ear buds  46  may include a heart rate sensor configured to sense a person&#39;s heart rate when a person is wearing the head phones, the clothing  48  may include sensors such as perspiration sensors, climate sensors, and heart sensors for measuring the intensity of a person&#39;s workout, and the exercise machine  50  may include a camera mounted on a portion thereof for gathering facial images of a user so that the machine  50  may thereby determine whether a particular facial expression is indicative of a user struggling to keep the pace set by the exercise machine  50  and/or an NFC element to e.g. pair the machine  50  with the CE device  12  and hence access a database of preset workout routines, and the kiosk  52  may include an NFC element permitting entry to a person authenticated as being authorized for entry based on input received from a complimentary NFC element (such as e.g. the NFC element  36  on the device  12 ). Also note that all of the devices described in reference to  FIG. 1 , including a server  54  to be described shortly, may communicate with each other over the network  22  using a respective network interface included thereon, and may each also include a computer readable storage medium that may not be a carrier wave for storing logic and/or software code in accordance with present principles. 
         [0037]    Now in reference to the afore-mentioned at least one server  54 , it includes at least one processor  56 , at least one tangible computer readable storage medium  58  that may not be a carrier wave such as disk-based or solid state storage, and at least one network interface  60  that, under control of the processor  56 , allows for communication with the other CE devices of  FIG. 1  over the network  22 , and indeed may facilitate communication therebetween in accordance with present principles. Note that the network interface  60  may be, e.g., a wired or wireless modem or router, WiFi transceiver, or other appropriate interface such as, e.g., a wireless telephony transceiver. 
         [0038]    Accordingly, in some embodiments the server  54  may be an Internet server, may facilitate fitness coordination and/or data exchange between CE device devices in accordance with present principles, and may include and perform “cloud” functions such that the CE devices of the system  10  may access a “cloud” environment via the server  54  in example embodiments to e.g. stream music to listen to while exercising and/or pair two or more devices (e.g. to “throw” music from one device to another). 
         [0039]      FIG. 2  shows a more specific example of a system according to the general principles above. A CE device  70  may be embodied as a wristwatch as shown (or a mobile telephone or other portable CE device or combination of devices) and may include one or more microprocessors  72  accessing one or more computer readable storage media  74  to output visible information to the wearer on a display  76 . Speakers also may be provided to output audible information. A position sensor such as a GPS sensor  78  may provide position information to the processor  72 , from which the processor  72  can calculate a speed over an interval of time ΔT using the equation speed=distance/ΔT. 
         [0040]    The processor  72  also can receive information from Internet servers discussed further below using a wireless network interface  80  such as a WiFi or telephony interface. The processor  72  may communicate with nearby devices such as the biometric sensors discussed further below and such as audio headphones  81  using, for example, a Bluetooth transceiver  82  or a radiofrequency identification (REM) transceiver or other wireless and typically short range (&lt;100 meters in useful transmission range) transceiver. User input of, e.g., recent food and beverage intake may be received on an input device  84  such as a keypad, microphone coupled to voice entry software, touch display, etc. The processor  72  may also access other information stored on the computer readable storage media  74  as received from another CE device or Internet server using one or more of the transceivers above. For example, the processor  72  may access calendar information of the user that lists future meetings and events for which the user is scheduled. 
         [0041]    As discussed above, the processor  72  can receive information from various Internet servers or other network servers by means of the network interface  80 . For example, the processor  72  can receive map information from a map server  86  from which, knowing its position from signals from the position sensor  78 , the processor  72  can ascertain the elevation, slope, and other terrain information pertaining to the present location of the CE device  70 . 
         [0042]    Also, the processor  72  can receive local weather information from a weather server  88 . The weather server  88  may access one or more of a humidity sensor  90 , a temperature sensor  92 , a barometer  94 , and a wind sensor  96  and, in response to receiving a query from the processor  72  using the current location of the CE device  70  as derived from the position sensor  78  as an automatically uploaded entering argument, provide local weather conditions to the processor  72 . The signals from the servers may be received by the CE device processor  72  through the appropriate communication interface and stored on the computer readable media  74  and/or on local cache memory associated with the processor  72 , for processing of the information through the registers of the processor  72  according to description herein to provide output on the display  76  and/or headphones  81  or other output device. 
         [0043]    In addition to accessing information from network servers, the processor  72  of the CE device  70  may access information from one or more biometric sensors that can be worn by or can otherwise be engaged with the user of the CE device  70 . A heart rate sensor  98  may be provided as an example in which signals from a pulse sensor  100  are provided to the CE device  70  through a wireless transceiver  102  such as but not limited to a Bluetooth transceiver under control of one or more processors  104  accessing one or more computer readable media  106 . The signals from the biometric sensor may be received by the CE device processor  72  through the appropriate communication interface and stored on the computer readable media  74  and/or on local cache memory associated with the processor  72 , for processing of the information through the registers of the processor  72  according to description herein to provide output on the display  76  and/or headphones  81  or other output device. 
         [0044]    A stride sensor  108  may be provided as another example in which signals from a stride sensor  110  (which may include, e.g., an accelerometer and/or gyroscope and/or force sensing resistor other jolt-sending or pressure-sensing device) are provided to the CE device  70  through a wireless transceiver  112  such as but not limited to a Bluetooth transceiver under control of one or more processors  114  accessing one or more computer readable media  116 . The signals from the biometric sensor  108  may be received by the CE device processor  72  through the appropriate communication interface and stored on the computer readable media  74  and/or on local cache memory associated with the processor  72 , for processing of the information through the registers of the processor  72  according to description herein to provide output on the display  76  and/or headphones  81  or other output device. 
         [0045]    A sleep rate sensor  118  may be provided as another example (typically sensing sleep prior to exercise and data from which is stored by the CE device  70  for later retrieval according to principles discussed below) in which signals from a sleep quality sensor  120  (which may include an actigraphy-type mechanism) are provided to the CE device  70  through a wireless transceiver  122  such as but not limited to a Bluetooth transceiver under control of one or more processors  124  accessing one or more computer readable media  126 . The signals from the biometric sensor  118  may be received by the CE device processor  72  through the appropriate communication interface and stored on the computer readable media  74  and/or on local cache memory associated with the processor  72 , for processing of the information through the registers of the processor  72  according to description herein to provide output on the display  76  and/or headphones  81  or other output device. 
         [0046]    Other biometric sensors may be provided, including a skin temperature sensor  128  that has onboard sensing, processing, and transceiving components similar to those discussed above in relation to other biometric sensors. The biometric sensors may be mounted on the CE device  70 , fitness devices such as treadmills, mobile telephones, clothing worn by the user, or even other devices and/or people in the same location as the user at the same time as the user. 
         [0047]      FIG. 3  shows logic in which factors from multiple sources are combined to output an accurate effort monitoring output. As discussed further below, these factors can include personal biometrics such as instantaneous heart rate, skin temperature, pace (as derived from position signals per above description, e.g.,), stride length, and stride cadence. The factors also can include the duration of the exercise activity (as accessed from the internal processor clock of the CE device  70 , for instance), location data such as position, absolute altitude, elevation gain (as derived from downloaded map data from the map server, for example), and terrain (type of surface for running as derived from downloaded map data). The factors may also include weather factors such as wind speed and direction, humidity, temperature, barometric pressure, and sun or cloud cover as derived from downloaded information from the weather server. Still further, the factors can include life context factors such as food intake as obtained from user input, stress levels as inferred from a number and frequency of meetings on the user&#39;s calendar data for example, and knowing the user&#39;s prior behavior as learned by the processor  72 . 
         [0048]    Accordingly, at block  130  in  FIG. 3  the CE device  70  in  FIG. 2  receives biometric information from one or more of the sensors shown in  FIG. 2 . Weather information from, e.g., the weather server  88  is received at block  132  and location information is received from the position sensor  78  at block  134 . From this, the user&#39;s distance run and pace over an exercise period can be determined from the above. 
         [0049]    Map and terrain information may be received at block  136  from, e.g., the map server  86 , and user-input information can be received at block  138  by means of, e.g., the user input device  84  indicating food and beverage intake of the user for the past N hours. Lifestyle information as derived from, e.g., a number of upcoming or immediately past meetings within a threshold time period (for instance, within the past or future 24 hours) can be retrieved from calendar information or elsewhere at block  140 . 
         [0050]    Weights for each factor may be applied at block  142  if desired, with each factor having its own respective weight and with some factors optionally having the same weights as other factors, or with each factor having its own unique weight. The weights can be positive or negative, e.g., for a run up a slope the weight accorded to a slope factor may be positive while for a run down a slope the weight can be negative. An effort level and/or coaching tips are output at block  144  based on the weighted combined factors. 
         [0051]    An example of the above now follows. 
         [0052]    A baseline effort indicator may be established as a number between 0-100 based on the distance and pace (speed) of the workout. The longer the distance and the faster the pace, the higher the baseline number. Note that each baseline number for each user may be established for that user by averaging the first several workout times and distances and paces, so that a baseline for one user may not be the same as the baseline for another user. 
         [0053]    That baseline number is then adjusted upwardly for factors that increase the difficulty of the workout and decreased downwardly for factors the decrease the difficulty of the workout. As examples: 
         [0054]    For average workout heart rates in excess of a test value such as but not limited to a median rate or average rate or other test value, which can be empirically determined if desired, add A points (multiplied if desired by a heart rate weighting factor) to the baseline number, wherein A, like the other adjustment “points” referred to herein, can be an integer. For average workout heart rates below a median rate, subtract A points (multiplied if desired by a heart rate weighting factor) to the baseline number. The adjustment points “A”, like the other adjustment points discussed below and designated by letters of the alphabet, can vary with the amount of excess/shortfall between the measured factor and the median. For example, the magnitude of “A” can increase (or decrease) linearly with the magnitude of the difference between the median and the measured value. Also, the median to which an excessive measurement value is compared may be the same as or different from the median to which a deficient measurement value is compared. Average values may be used, e.g., an average elevation or slope over the course of an exercise run or ride may be used. Or, instantaneous values may be used and the baseline adjusted and output updated accordingly. 
         [0055]    For peak workout heart rates in excess of a median rate, which can be empirically determined if desired, add B points (multiplied if desired by a peak heart rate weighting factor) to the baseline number. For peak workout heart rates below a median rate, subtract B points (multiplied if desired by a peak heart rate weighting factor) to the baseline number. 
         [0056]    For skin temperature in excess of a median, which can be empirically determined if desired, add C points (multiplied if desired by a skin temperature weighting factor) to the baseline number. For skin temperature below a median, which can be empirically determined if desired, subtract points (multiplied if desired by a skin temperature weighting factor) from the baseline number. 
         [0057]    For stride length in excess of a median, which can be empirically determined if desired, add D points (multiplied if desired by a stride length weighting factor) to the baseline number. For stride length below a median, which can be empirically determined if desired, subtract points D (multiplied if desired by a stride length weighting factor) from the baseline number. 
         [0058]    For stride cadence in excess of a median, which can be empirically determined if desired, add E points (multiplied if desired by a stride cadence weighting factor) to the baseline number. For stride cadence below a median, which can be empirically determined if desired, subtract E points (multiplied if desired by a stride length weighting factor) from the baseline number. 
         [0059]    For sleep quality in excess of a median, which can be empirically determined if desired, subtract F points (multiplied if desired by a sleep quality weighting factor) from the baseline number. For sleep quality below a median, which can be empirically determined if desired, add F points (multiplied if desired by a sleep quality weighting factor) from the baseline number. 
         [0060]    For ambient temperature in excess of a median, which can be empirically determined if desired, add G points (multiplied if desired by an ambient temperature weighting factor) to the baseline number. For ambient temperature below a median, which can be empirically determined if desired, subtract G points (multiplied if desired by an ambient temperature weighting factor) from the baseline number. 
         [0061]    For ambient humidity in excess of a median, which can be empirically determined if desired, add H points (multiplied if desired by a humidity weighting factor) to the baseline number. For ambient humidity below a median, which can be empirically determined if desired, subtract H points (multiplied if desired by a humidity weighting factor) from the baseline number. 
         [0062]    For ambient pressure in excess of a median, which can be empirically determined if desired, add I points (multiplied if desired by an ambient pressure weighting factor) to the baseline number. For ambient pressure below a median, which can be empirically determined if desired, subtract I points (multiplied if desired by an ambient pressure weighting factor) from the baseline number. 
         [0063]    For the speed vector of the ambient wind that is directly against the user&#39;s direction of travel in excess of a median, which can be empirically determined if desired, add K points (multiplied if desired by an ambient wind weighting factor) to the baseline number. For a similar speed vector going with the user, subtract K points (multiplied if desired by an ambient wind weighting factor) from the baseline number. 
         [0064]    For an upward slope of terrain in the direction of the user&#39;s travel in excess of a median, which can be empirically determined if desired, add L points (multiplied if desired by a slope weighting factor) to the baseline number. For a downward slope, subtract L points (multiplied if desired by a slope weighting factor) from the baseline number. 
         [0065]    For a difficult terrain surface in excess of a median, which can be empirically determined if desired, add M points (multiplied if desired by a terrain weighting factor) to the baseline number. For an easy terrain, subtract M points (multiplied if desired by a terrain weighting factor) from the baseline number. 
         [0066]    For a caloric intake within the last Z hours below a median which can be empirically determined if desired, add N points (multiplied if desired by a calorie weighting factor) to the baseline number. For a caloric intake within the last Z hours above a median which can be empirically determined if desired, subtract N points (multiplied if desired by a calorie weighting factor) from the baseline number. 
         [0067]    For a number of meetings within the last Z hours below a median which can be empirically determined if desired, subtract P points (multiplied if desired by a stress weighting factor) from the baseline number. For a number of meetings within the last Z hours above a median which can be empirically determined if desired, add P points (multiplied if desired by a stress weighting factor) to the baseline number. 
         [0068]    For a number of meetings in the next Z hours below a median which can be empirically determined if desired, subtract Q points (multiplied if desired by a stress weighting factor) from the baseline number. For a number of meetings in the next Z hours above a median which can be empirically determined if desired, add Q points (multiplied if desired by a stress weighting factor) to the baseline number. 
         [0069]    For an elevation in excess of a median, which can be empirically determined if desired, add R points (multiplied if desired by an elevation weighting factor) to the baseline number. For elevation below a median, which can be empirically determined if desired, subtract R points (multiplied if desired by an elevation weighting factor) from the baseline number. 
         [0070]    When all of the adjustments to the baseline number, such as some or all of the above, are made, an adjusted baseline number is arrived at. The magnitude of the adjusted baseline number may then be used to output an effort level and/or coaching tips. In one example, the magnitude of the adjusted baseline number may be used as entering argument in a table lookup as follows: 
         [0000]    
       
         
               
               
               
             
           
               
                   
               
               
                 Adjusted 
                   
                   
               
               
                 Baseline Number 
                 Effort Level 
                 Coaching Tip 
               
               
                   
               
             
             
               
                  0-10 
                 very low 
                 “need a lot more from you!” 
               
               
                 10-20 
                 moderately low 
                 “try harder” 
               
               
                 20-30 
                 low 
                 “try a little harder” 
               
               
                 30-40 
                 minimally low 
                 “effort not quite there yet” 
               
               
                 40-50 
                 below average 
                 “almost average” 
               
               
                 50-60 
                 above average 
                 “doing OK today” 
               
               
                 60-70 
                 minimally high 
                 “effort higher than expected” 
               
               
                 70-80 
                 high 
                 “you are cranking it today!” 
               
               
                 80-90 
                 moderately high 
                 “doing more than enough!” 
               
               
                  90-100 
                 very high 
                 “take it easy Secretariat!” 
               
               
                   
               
             
          
         
       
     
         [0071]      FIG. 4  shows that a runner  200  wearing the CE device  70  shown in  FIG. 2  formerly would not have understood, as indicated by the thought balloon  202 , why a workout felt harder than the CE device absent present principles indicated. However, when accounting according to present principles for biometric readings  204 , terrain and position and slope  206 , climate conditions  208 , and life context conditions  210 , an adjusted output  212  may be presented on the CE device  70  visibly and/or audibly correctly reflecting the combined factor effort level of the runner  200 . 
         [0072]    With no particular reference to any figure, it is to be understood that lactate sensors may also be included on, and/or in communication with, the CE devices described herein for sensing lactate levels, which can be e.g. measured in sweat, to thus determine an effort level in accordance with present principles and accordingly be another biometric parameter to be factored into a determination/adjustment of a baseline in accordance with present principles. Thus, e.g., for lactate levels in excess of a median, which can be empirically determined if desired, XYZ points may be added as set forth herein (multiplied if desired by a lactate level weighting factor) to the baseline number. For lactate levels below a median, which can be empirically determined if desired, points may be subtracted (multiplied if desired by a lactate level weighting factor) from the baseline number. 
         [0073]    While the particular Combining Data Sources to Provide Accurate Effort Monitoring is herein shown and described in detail, it is to be understood that the subject matter which is encompassed by the present invention is limited only by the claims.