CA2822708A1 - Sensory user interface - Google Patents

Abstract

Techniques for sensory user interface are described, including receiving a sensory input at a sensor coupled to a wearable device, converting the sensory input into data using the sensor and the processor, processing, the data to generate a representation of a state, evaluating the representation to determine if an action is indicated, and performing the action if indicated based on an evaluation of the representation.

Description

SENSORY USER INTERFACE
FIELD
The prcscnt invention relates generally to electrical and electronic hardware, computer software, human-computing interfaces, wired and wireless network communications, and computing devices. More specifically, techniques for a sensory user interface arc described.
BACKGROUND
With thc advent of greater computing capabilities in smaller personal and/or portable form factors and an increasing number of applications (i.c., computer and Internet software or progratns) for different uses, consumers (i.e., users) have access to large amounts of personal data. Information and data are often readily available, but poorly captured using conventional data capture devices. Conventional devices typically lack capabilities that can capture, analyze, communicate, or use data in a contextually-meaningful, comprehensive, and efficient manner.
Further, conventional solutions arc often limited to specific individual purposes or uses, demanding that users invest in multiple devices in ordcr to perform different activities (e.g., a sports watch for tracking timc and distance, a GPS receiver for monitoring a hike or nin. a cyclometer for gathering cycling data, and others). Although a wide range of data and information is available. conventional devices and applications fail to provide effective solutions that comprehensively capture data for a given user across numerous disparate activities.
Some conventional solutions combine a small number of discrete functions.
Functionality for data capture, processing, storage, or communication in conventional devices such as a watch or timer with a heart ratc monitor or global positioning system ("GPS") receiver arc available conventionally, but arc expensive to manufacture and purchase.
Other conventional solutions for combining personal data capture facilities oftcn present numerous design and manufacturing problems such as size restrictions. specialized materials requirements, lowered tolerances for defects such as pits or holes in coverings for water-resistant or waterproof devices, unreliability, higher failure rates, increased manufacturing time, and expense.
Subsequently, conventional devices such as fitness watches, hcart rate monitors, GPS-enabled fitness monitors, health Monitors (e.g., diabetic blood sugar testing units), digital voice recorders, pedometers, altimeters, and othcr conventional personal data capturc devices arc generally !manufactured for conditions that occur in a single or small groupings of activities.
Generally, if the number of activities performed by conventional personal data capture devices increases, there is a corresponding risc in design and manufacturing requirements that results in significant consumer expense, which eventually becomes prohibitive to both investment and commercialization. Further, conventional manufacturing techniques are often limited and ineffective at meeting increased requirements to protect sensitive hardware, circuitry, and other components that arc susceptible to damage, but which arc required to perform various personal data capturc activities. As a conventional example, sensitive electronic components such as printed circuit board assemblies ("PCBA"), sensors, and computer memory (hereafter "memory") can be significantly damaged or destroyed during manufacturing processes where overmoldings or layering of protective material occurs using techniques such as injection molding, cold molding, and others. Damaged or destroyed items subsequently raises the cost of goods sold and can deter not only investment and commercialization, but also innovation in data capturc and analysis technologies, which are highly compelling fields of opportunity.
Thus, what is needed is a solution for sensory input and processing without the limitations of conventional techniques.
BRIEF DESCRIPTION OF THE DRAWINGS
Various embodiments or examples ("examples") arc disclosed in the following detailed description and the accompanying drawings:
FIG. 1 illustrates an exemplary data-capable strapband system;
FIG. 2A illustrates an exemplary wearable device and platform for scnsory input;
FIG. 2B illustrates an alternative exemplary wearable device and platform for sensory input;
FIG. 3 illustrates sensors for usc with an exemplary data-capable strapband;
FIG. 4 illustrates an application architecture for an exemplary data-capable strapband;
FIG. SA illustrates representative data types for use with an exeinplary data-capable strapband;
FIG. 5B illustrates representative data types for use with an exemplary data-capable strapband in fitness-related activities;
FIG..5C illustrates representative data types for use with an exemplary data-capablc strapband in sleep management activities;
FIG. 5D illustrates representative data types for usc with an exemplary data-capable strapband in medical-related activities;
FIG. SE illustrates representative data types for use with an exemplary data-capable strapband in social media/networking-related activities;
FIG. 6 illustrates a transition between modes of operation.of a strapband in accordance = with various embodiments;
FIG. 7A illustrates a perspective view of an exemplary data-capablc strapband:
FIG. 7B illustrates a sidc view of an exemplary data-capable strapband;
FIG. 7C illustrates another sidc view of an exemplary data-capable strapband;
FIG. 7D illustrates a top view of an exemplary data-capable strapband;
FIG. 7E illustrates a bottom view of an exemplary data-capable strapband;
FIG. 7F illustrates a front view of an exemplary data-capable strapband;
FIG. 7G illustrates a rear view of an exemplary data-capablc strapband;
FIG. RA illustrates a perspective view of an exemplary data-capable strapband;

FIG. 8B illustrates a sidc view of an exemplary data-capablc strapband;

2 FIG. 8C illustrates another side view of an exemplary data-capable strapband;
FIG. 8D illustrates a top vicw of an exemplary data-capable strapband;
FIG. 8E illustrates a bottom view of an exemplary data-capable strapband:
FIG. 8F illustrates a front view of an exemplary data-capable strapband;
FIG. 8G illustrates a rear view of an exemplary data-capable strapband;
FIG. 9A illustrates a perspective view of an exemplary data-capable strapband;

FIG. 9B illustrates a side view of an exemplary data-capable strapband;
FIG. 9C illustrates another sidc view of an exemplary data-capable strapband;
FIG. 9D illustrates a top view of an exemplary data-capable strapband;
1() FIG. 9E illustrates a bottom view of an exemplary data-capable strapband;
FIG. 9F illustmtcs a front view of an exemplary data-capablc strapband;
FIG. 90 illustrates a rear view of an exemplary data-capable strapband:
FIG. 10 illustrates an exemplary computer systcm suitable for use with a data-capable strapband;
FIG. I I depicts a variety of inputs in a specific example of a strapband, such as a data-capable strapband, according to various embodiments;
FIGs. 12A to I2F depict a variety of motion signatures as input into a strapband, such as a data-capable strapband, according to various embodiments;
FIG. 13 depicts an inference engine of a strapband configured to detect an activity and/or a mode bascd on monitored motion, according to various embodiments;
FIG. 14 depicts a representative implementation of one or more strapbands and equivalent devices, as wearable devices, to form unique motion profiles, according to various embodiments;
FIG. 15 depicts an example of a motion capture manager configured to capturc motion and portions thereof, according to various embodiments;
FIG. 16 depicts an example of a motion analyzer configured to evaluate !notion-centric events, according to various embodiments;
FIG. 17 illustrates action and event processing during a mode of operation in accordance with various embodiments;
FIG. 18A illustrates an exemplary wearable device for scnsory uscr interface;
FIG. 18B illustrates an alternative exemplary wearable device for sensory.user interface;
FIG. I8C illustrates an exemplary switch rod to bc used with an exemplary wearable device;
FIG. 18D illustrates an exemplary switch for use with an exemplary wearable device;
and FIG. 18E illustrates an exemplary scnsory uscr interface.

3 DETAILED DESCRIPTION
Various embodiments or examples may bc implemented ill numerous ways, including as a system, a process, an apparatus, a uscr interface, or a series of program instructions on a computer readable medium such as a computer readable storage medium or a computer network where the program instructions arc sent over optical, electronic, or wireless communication links. In 'general, operations of disclosed processes may be perfornied in an arbitrary order, unless otherwise provided in the claims.
A detailed description of one or morc examples is provided below along with accompanying figures. The detailed description is provided in connection with such examples, but is not limited to any particular example. Thc scope is limited only by the claims and numerous alternatives, modifications, and equivalents arc encompassed.
Numerous specific details are set forth in the following description in ordcr to provide a thorough understanding.
These details arc provided for thc purpose of example and the described techniques may be practiced according to the claims without some or all of these specific details. For clarity, technical material that is known in the technical fields related to thc examples has not been described in detail to avoid unnecessarily obscuring the description.
FIG. 1 illustrates an exemplary data-capable strapband system. Here, system includes network 102, strapbands (hereafter "bands") 104-112, server 114, mobile computing device 115, mobile communications device l 18, computer 120, laptop 122, and distributed = sensor 124. Although used interchangeably, "strapband" and -band" may be used to refer to the same or substantially siinilar data-capable device that may be worn as a strap or band around an arm, leg, ankle, or other bodily appendage or feature. In other examples.
bands 104-112 may be attached directly or indirectly to other items, organic or inorganic, animate, or static. In still other examples, bands 104-112 may be used differently.
As described above, bands 104-112 may bc implemented as wearable personal data or data capture devices (e.g., data-capable devices) that arc worn by a user around a wrist, ankle, arm, car, or other appendage, or attached to thc body or affixed to clothing.
One or more facilities, sensing elements, or sensors, both active and passive, may be implemented as part of bands 104-112 in order to capture various types of data from different sources. Temperature, environmental, temporal, motion, electronic, electrical, chemical, or other typcs of sensors (including those described below in connection with FIG. 3) may be used in order to gather varying amounts of data, which may be configurable by a uscr, locally (e.g., using user interface facilities such as buttons, switches, motion-activated/detected command structures (e.g., accelerometer-gathered data from user-initiated motion of bands 104-112), and others) or remotely (e.g., entering rules or parametcrs in a website or graphical user interface ("GUI") that may be used to modify control systcms or signals in firmware, circuitry, hardware, and software implemented (i.e., installed) on bands 104-112). In soine examples, a user interface may bc any tyix of human-computing interface (e.g., graphical, visual, audible, hawk, or any other type of

4

5 interface that communicates information to a user (i.e., wearer of bands 104-112) using, for example, noise, light, vibration, or other sourccs of energy and data generation (e.g., pulsing vibrations to represent various types of signals or meanings, blinking lights, and the like, without limitation)) implemented locally (i.e., on or coupled to onc or more of bands 104-112) or remotely (i.e., on a device other than bands 104-112). In other examples, a wearable device such as bands 104-112 may also be implemented as a uscr interface configured to receive and provide input to or from a user (i.e., wearer). Bands 104-112 may also be implemented as data-capable devices that are configured for data communication using various types of communications infrastnicturc and media, as described in greater detail below.
Bands 104-112 may also be wearable, personal, non-intrusive, lightweight devices that arc configured to gather large amounts of personally relevant data that can bc uscd to improve user health, fitness levels, medical conditions, athletic performance, sleeping physiology, and physiological conditions, or used as a sensory-based uscr interface ("Ul") to signal social-related notifications specifying the state of the user through vibration, heat, lights or othcr sensory bascd notifications. For example, a social-related notification signal indicating a user is on-line can he transmitted to a recipient, who in turn, receives the notification as, for instance, a vibration.
Using data gathered by bands 104-112, applications may be used to perform various analyses and evaluations that can generate information as to a person's physical (e.g., healthy, sick, weakened, or other states, or activity level), emotional, or mental state (e.g., an elevated body temperature or heart rate may indicate stress, a lowered heart rate and skin temperature, or reduced movement (excessive sleepine), may indicate physiological depression caused by -exertion or other factors, chemical data gathered from evaluating outgassing from the skin's surface may be analyzed to determine whcthcr a person's diet is balanced or if various nutrients arc lacking, salinity detectors may be evaluated to determine if high, lower, or proper blood sugar levels are present for diabetes management, and others). Generally, bands 104-1 12 may be configured to gather from sensors locally and remotely.
As an example, band 104 may capturc (i.e., record, store, communicate (i.c., scnd or receive), process, or the like) data from various sources (i.c., sensors that arc organic (i.c., installed, integrated, or othenvise implemented with band 104) or distributed (e.g., microphones on mobile computing dcvicc 115, mobile communications device 118, computer 120, laptop 122, distributed sensor 124, global positioning system ("GPS") satellites (in low, mid, or high earth orbit), or others, without limitation)) and exchange data with onc or more of bands 106-112, server 114, mobile computing device 115, mobile communications device 118, computer 120, laptop 122, and distributed scnsor 124. As shown here, a local sensor may be one that is incorporated, integrated, or otherwise implemented with bands 104-112. A
remote or distributed scnsor (e.g., mobile computing device I l 5, mobile communications device 118, computer 120, laptop 122, or, generally, distributed scnsor 124) may be scnsors that can bc accessed, controlled, or otherwise uscd by bands 104-112. For example, band 112 may bc configured to control devices that arc also controlled by a given user (e.g., mobile computing device 115, mobile communications device 118, computcr 120, laptop 122, and distributed scnsor 124). For example, a microphone in mobile communications device 118 may bc used to detect, for example, ambient audio data that is used to help identify a person's location, or an car clip (e.g., a headset as described below) affixed to an car may be uscd to record pulse or blood oxygen saturation levels. Additionally, a sensor implemented with a screen on mobile computing device 115 may be used to read a uscr's temperature or obtain a biometric signature while a user is interacting with data. A further example may include using data that is observed on computer 120 or laptop 122 that provides information as to a uscr's online behavior and thc type of content that she is viewing, which may be used by bands 104-112. Regardless of the type or location of scnsor uscd, data may be transferred to bands 104-112 by using, for example, an =
analog audio jack, digital adapter (e.g., USB, mini-USB), or other, without limitation, plug, or othcr type of connector that may be used to physically couple bands 104- 112 to another device or system for transferring data and, in some examples, to provide power to recharge a battery (not shown). Alternatively, a wireless data communication interface or facility (e.g., a wireless radio that is configured to comtnunicate data from bands 104-112 using one or more data comtnunication protocols (e.g., IEEE 802.11a/b/Wn (WiFi), WiMax, ANT", ZigBect, Bluetooth*, Near Field Communications ("NFC"), and others)) may be used to receive or transfer data. Further, bands 104-112 may be configured to analyze, evaluate, modify, or otherwise use data gathered, either directly or indirectly.
In some examples, bands 104-112 may be configured to share data with each other or with an intermediary facility, such as a database, websitc, web service, or the like, which may be iMplemented by server 114. In some embodiments, server 114 can be operated by a third party providing, for example, social media-related services. Bands 104-112 and other related devices may exchange data with each other directly, or bands 104-112 may exchange data via a third party server, such as a third party like Facebook , to provide social-media related services.
ExaThples of third party servers include servers for social networking services, including, but not limited to, services such as Facebooke, Yahoo! [M.", GTalk.", MSN Messenger"
Twitter and othcr private or public social networks. The exchanged data may include personal 20 physiological data and data derived from sensory-based uscr intcrfaccs ("UI").
Server 114, in some examples, may be implemented using onc or more processor-based computing devices or networks, including computing clouds, storage arca nctworks ("SAN"), or the likc. As shown, bands 104-112 may bc uscd as a personal data or arca nctwork (e.g., -PDN" or -PAN") in which = data relevant to a given user or band (e.g., onc or more of bands 104-1 12) may be shared. As shown here, bands 104 and 112 may be configured to exchange data with each other over network 102 or indirectly using server 114. Users of bands 104 and 112 may dircct a wcb browser hostcd on a computer (e.g., computcr 120, laptop 122, or thc like) in order to access, view, modify, or perfonn other operations with data capturcd by bands 104 and 112. For

6 example, two runners using bands 104 and 112 may be geographically remote (e.g., users arc not geographically in close proximity locally such that bands being used by each user arc in direct data communication), but wish to sharc data regarding their race times (pre, post, or in-racc), personal records (i.c., "PR"), target split times, results, performance characteristics (e.g., target heart rate, target V02 max, and othcrs), and other information. If both runners (i.e., bands 104 and 112) arc engaged in a race on the same day, data can be gathered for comparative analysis and other uses. Further, data can be shared in substantially real-time (taking into account any latencies incurred by data transfer rates, network topologies. or other data network factors) as well as uploaded after a given activity or event has been performed. In other words, data can bc captured by the uscr as it is worn and configured to transfer data using, for example, a wireless network connection (e.g., a wireless network interface card, wireless local arca nctwork ("LAN") card, cell phone, or the like. Data may also be shared in a temporally asynchronous manner in which a wired data connection (e.g., an analog audio plug (and associated software or firmware) configured to transfcr digitally encoded data to encoded audio data that may be transferred between bands 104-112 and a plug configured to receive, encode/decode, and process data exchanged) may bc uscd to transfer data from one or more bands l 04-112 to various destinations (e.g., another of bands 1()4-112, server 114, mobile computing device 115.
mobile communications device 118, computer 120, laptop 122, and distributed sensor 124).
Bands 104-112 may be implemented with various types of wired and/or wireless communication facilities and arc not intended to be limited to any specific technology. For example, data may be transferred from bands 104-112 using an analog audio plug (e.g., TRRS, TRS, or others). In other examples, wireless communication facilities using various types of data communication protocols (e.g., WiFi, Bluetooth), ZigBec@, ANT'', and others) may be itnplemented as part of bands 104-112, which may include circuitry, firmware, hardware, radios, antennas, processors, microprocessors. memories, or othcr electrical, electronic, mechanical, or physical elements configured to enable data communication capabilities of various types and characteristics.
As data-capable devices, bands 104-112 may be configured to collect data from a wide range of sources, including onboard (not shown) and distributed sensors (e.g., server 114, mobile computing device 115, mobile communications device 118, computer 120, laptop 122, and distributed scnsor 124) or other bands. Some or all data captured may be personal.
sensitive, or confidential and various techniques for providing secure storage and access may bc implemented. For example, various typcs of sccurity protocols and algorithms may be used to encode data stored or accessed by bands 104-112. Examples of sccurity protocols and algorithms include authentication, encryption, encoding, private and public key infrastructure, passwords, checksums, hash codcs and hash functions (e.g., SHA, SHA-1, MD-5, and the like), or othcrs may bc used to prevent undesired access to data captured by bands 104-112. In other examples, data security for bands 104-112 may bc impletnented differently.

7 Bands 104-112 may be used as personal wearable, data capture devices that, when wom, arc configured to identify a specific, individual user. By evaluating calptured data such as motion data from an accelerometer, biomctric data such as heart rate, skin galvanic rcsponsc, and other biometric data, and using analysis techniques, both long and short-term (e.g., software packages or modules of any type, without limitation), a user may have a unique pattern of behavior or motion and/or biometric responses that can be used as a signature for identification.
For example, bands 104-112 may gather data regarding an individual person's gait or other unique biometric, physiological or behavioral characteristics. Using, for example, distributed sensor 124, a biometric signature (e.g., fingerprint, retinal or iris vascular pattcrn, or others) may bc gathered and transmitted to bands 104-112 that, when combined with other data, determines that a given user has been properly identified and, as such, authenticated.
When bands 104-112 arc wom, a user may be identified and authenticated to enable a variety of other functions such as accessing or modifying data, enabling wired or wireless data transmission facilities (i.c., allowing the transfer of data from bands 104- 112), modifying functionality or functions of bands 104-112, authenticating financial transactions using stored data and information (e.g., credit card, PIN, card sccurity numbers, and thc like), running applications that allow for various operations to be performed (e.g., controlling physical security and access by transmitting a security code to a reader that, when authenticated, Unlocks a door by turning off cun-ent to an electromagnetic lock, and others), and othcrs. Different functions and operations beyond those described may be perfornied using bands 104-112, which can act as secure, personal, wearable, data-capable devices. The number, typc, function, configuration, specifications, structure, or other features of system 100 and the above-described elements may bc varied and are not limited to thc examples provided.
FIG. 2A illustrates an exemplary wearable device and platform for sensory input. Here.
band (i.c., wearable device) 200 includes bus 202, processor 204, memory 206, vibration source 208, accelerometer 210, scnsor 212, battery 214, and communications facility 216. In some examples, the quantity, type, function, structure, and configuration of band 200 and the elements (e.g., bus 202, processor 2()4, memory 206, vibration source 208, accelerometer 210, sensor 212, battery 214, and communications facility 216) shown may be varied and are not limited to thc examples provided.' As shown, proccssor 204 may be implemented as logic to provide control functions and signals to memory 206, vibration source 208, accelerometer 210, scnsor 212, battcry 214, and communications facility 216. Processor 204 may bc implemented using any typc of processor or microprocessor suitable for packaging within bands 104-112 (FIG. 1).
Various types of microprocessors may be used to provide data processing capabilities for band 200 and are not limited to any specific type or capability. For example, a MSP430F5528-type microprocessor manufactured by Texas Instruments of Dallas, Tcxas may bc configured for data communication using audio toncs and enabling thc usc of an audio plug-and-jack system (e.g., TRRS, TRS, or others) for transferring data captured by band 200. Further, different proccssors

8 may be desired if other functionality (e.g., the type and number of sensors (e.g., sensor 212)) are varied. Data processed by processor 204 may bc storcd using, for example, memory 206.
In some examples, memory 206 may be implemented using various typcs of data storage technologies and standards, including, without limitation, read-only memory ("ROM"), random access memory ("RAM"), dynamic random access memory ("DRAM"), static random access memory (-SRAM"), static/dynamic random access memory ("SDRAM"), magnetic randoin access memory ("MRAM"), solid state, two and three-dimensional memories, Flash . and others. Memory 206 may also bc implemented using one or more partitions that are Configured for multiple types of data storage technologies to allow for non-modifiable (i.c., by a uscr) software to bc installed (e.g., fin-mare installed on ROM) while also providing for storage of capturcd.data and applications using, for example, RAM. Once captured ancUor storcd in memory 206, data may be subjected to various operations performed by othcr elements of band /00.
Vibration source 208, in some examples, may be implemented as a motor or other mechanical structure that functions to provide vibratory energy that is communicated through band 200. As an example, an application storcd on memory 206 may bc configured to monitor a clock signal from processor 204 in order to provide tiinekeeping functions to band 200. If an alarm is set for a desired time, vibration source 208 may be used to vibrate when thc desired time occurs. As another example, vibration source 208 may be coupled to a framework (not shown) or other structure that is used to translate or communicate vibratory energy throughout the physical structure of band 200. In other examples, vibration source 208 may be implemented differently.
Power may be stored in battery 214, which may bc implemented as a battery, battery module, power management module, or the like. Power may also be gathered from local power sources such as solar panels, therino-clectric generators, and kinetic energy generators, among others that are alternatives power sourccs to external power for a battery.
These additional sourccs can either power the system directly or can charge a battery, which, in turn, is used to power the system (e.g., of a strapband). In other words, battery 214 may include a rechargeable, expendable, replaceable, or other type of battery, but also circuitry, hardware, or softwarc that may be used in connection with in licu of proccssor 204 in order to provide power management, charge/recharging, sleep, or other functions. Further, battery 214 may bc implemented using various types of battery technologies, including Lithium Ion ("LI"), Nickel Metal Hydride ("NiMH"), or othcrs, without limitation. Powcr drawn as electrical current may be distributed from battery via bus 202, the latter of which may be implemented as deposited or formed circuitry or using other forms of circuits Or cabling, including flexible circuitry. Electrical current distributed &on) battery 204 and managed by processor 204 may be uscd by onc or morc of memory 206, vibration source 208, accelerometer 210, sensor 212, or communications facility 216.

9 As shown, various sensors may be used as input sources for data capturcd by band 200.
For example, accelerometer 2I() may bc used to dctcct a motion or other condition and convert it to data as measured across one, two, or three axes of motion. In addition to accelerometer 210, othcr sensors (i.e., scnsor 212) may be implemented to provide temperature, environmental, physical, chemical, electrical, or other types of sensory inputs. As presented here, sensor 212 may include one or multiple sensors and is not intended to be limiting as to the quantity or type of sensor implemented. Sensory input captured by band 200 using accelerometer 210 and sensor 212 or data requested from another sourcc (i.e., outside of band 200) may also be converted to data and exchanged, transferred, or otherwise communicated using communications facility 216.
As used herein, "facility" refers to any, some, or all of thc features and structures that arc used to implement a given sct of functions. For example, communications facility 216 may include a wireless radio, control circuit or logic, antenna, transceiver, receiver, transmitter, rcsistors, diodcs, transistors, or other elements that arc used to transmit and receive data from band 200.
In some examples, communications facility 216 may be implemented to provide a "wircd" data communication capability such as an analog or digital attachment, plug, jack, or the like to allow for data to be transferred. In othcr examples, communications facility 216 may be implemented to provide a wireless data communication capability to transmit digitally encoded data across one or more frequencies using various types of data communication protocols, without limitation. In still other examples, band 200 and the above-described elements may be varied in function, structure, configuration, or implementation and arc not limited to those shown and describcd.
FIG. 2B illustrates an alternative exemplary wearable device and platform for sensory input. Hcrc, band (i.e., wearable device) .220 includes bus 202, processor 204, memory 206, vibration source 208, accelerometer 210, sensor 212, battery 214, communications facility 216, switch 222, and light-emitting diodc (hereafter "LED") 224. Like-numbered and named clernents may be implemented similarly in function and structure to those described in prior examples. Further, the quantity, typc, function, structure, and configuration of band 200 and the elements (e.g., bus 202, proccssor 204, memory 206, vibration source 208, accelerometer 2l(), sensor 212, battcry 214. and communications facility 216) shown may be varied and arc not limited to thc examples provided.
In sonic examples, band 200 may bc implemented as an alternative structure to band 200 (FIG. 2A) dcscribcd above. For example, sensor 212 may bc configured to sense, detect, gather, or otherwise receive input (i.c., scnscd physical, chemical, biological, physiological, or psychological quantities) that, once received, may be converted into data and transferred to processor 204 using bus 202. As an example, temperature, heart rate, respiration rate, galvanic skin response (i.c., skin conductance response), muscle stiffness/fatigue, and other types of conditions or parameters may bc measured using scnsor 212, which may be implemented using onc or multiple scnsors. Further, sensor 212 is generally coupled (directly or indirectly) to band 220. As used herein, "coupled" may refer to a sensor being locally implemented on band 220 or remotely on, for example, another device that is in data communication with it.
Sensor 212 may be configured, in somc examples, to sense various types of environmental (e.g., ambient air temperature, barometric pressure, location (e.g., using GPS or other satellite constellations for calculating Cartesian or other coordinates on the carth's surface, micro-ccll network triangulation, or others), physical, physiological, psychological, or activity-based conditions in order to determine a state of a user of wearable device 220 (i.e., band 220).
In other examples, applications or firmware may be downloaded that, when installed, may be configured to change scnsor 212 in terms of function. Sensory input to scnsor 212 may bc uscd for various purposes such as measuring caloric burn rate, providing active (e.g., generating an alert such as vibration, audible, or visual indicator) or inactive (e.g., providing information, content, promotions, advertisements, or the like on a website, mobile 1,vebsite, or other location that is accessible using an account that is associated with a user and band 220) feedback, measuring fatigue (e.g., by calculating skin conductance response (hereafter "SCR") using sensor 212 or accelerometer 210) or other physical states, determining a mood of a user, and others, without limitation. As uscd herein, fccdback may be provided using a mechanism (i.c., feedback mechanism) that is configured to provide an alert or other indicator to a user. Various types of feedback mechanisms may be used, including a vibratory source, motor, light source (e.g., pulsating, blinking, or steady illumination), light emitting diode (e.g., LED 224), audible, audio, visual, haptic, or others, without limitation. Feedback mechanisms may provide sensory output of thc types indicated above via band 200 or, in other examples, using other devices that may be in data communication with it. For example, a driver may receive a vibratory alert from vibration source (e.g., motor) 208 when sensor 212 detects skin tautness (using, for example, accelerometer to dctcct muscle stiffness) that indicates she is falling asleep and, in connection with a GPS-scnsed signal, Wearable device 220 determines that a vehicle is approaching a divider, intersection, obstacle, or is accelerating/decelerating rapidly, and the like. Further, an audible indicator may be generated and sent to an car-worn communication device such as a Bluctooth0 (or other data communication protocol, near or far ficld) headset.
Other typcs of devices that have a data connection with wearable device 220 may also be used to provide sensory output to a user, such as using a mobile communications or computing device having a graphical user intcrfacc to display data or information associated with sensory input received by sensor 212.
In some examples, sensory output may be an audible tone, visual indication, vibration, or othcr indicator that can be provided by another device that is in data communication with band 220. In other examples, sensory output may bc a media file such as a song that is played when sensor 212 dctccts a given parameter. For example, if a uscr is running and sensor 212 detects a heart rate that is lower than thc recorded heart rate as measured against 65 previous runs, proccssor 204 may bc configured to generate a control signal to an audio device that begins playing an upbeat or high tempo song to the user in order to increase her heart rate and activity-based performance. As another example, sensor 212 and/or accelerometer 210 may sense various inputs that can bc measured against a calculated "lifeline" (e.g., LIFELINE") that is an abstract representation of a uscr's health or wellness. If sensory input to sensor 212 (or accelerometer 210 or any other sensor implemented with band 220) is received, it may be compared to thc user's lifeline or abstract representation (hereafter "representation") in order to determine whether feedback, if any, should be provided in order to modify the user's behavior.
A user may input a range of tolerance (i.e., a range within which an alert is not generated) or processor 204 may determine a range of tolerance to bc stored in memory 206 with regard to various sensory input. For example, if sensor 212 is configured to measure internal bodily temperature, a user may sct a 0.1 degree Fahrenheit range of tolerance to allow hcr body temperature to fluctuate between 98.5 and 98.7 degrees Fahrenheit before an alert is generated (e.g., to avoid heat stress, heat exhaustion, heat stroke, or the like).
Sensor 212 may also be implemented as multiple scnsors that are disposed (i.c., positioned) on oppositc sides of band 220 such that, when worn on a wrist or other bodily appendage, allows for the measurement of skin conductivity in ordcr to determine skin conductance response. Skin conductivity may be used to measure various types of parameters and conditions such as cognitive effort, arousal, lying, stress, physical fatigue due to poor sleep quality, emotional responses to various stimuli, and others.
Activity-based feedback may be given along with state-based feedback. In some examples, band 220 may be configured to provide feedback to a user in order to help him achieve a desired level of fitness, athletic performance, health, or wellness.
In addition to feedback, band 220 may also bc configured to provide indicators of use to a wearer during, before, or aftcr a given activity or state.
As used herein, various types of indicators (e.g., audible, visual, mechanical, or the like) may also be used in order to provide a sensory uscr interface. In other words, band 220 may be configured with switch 222 that can bc implemented using various types of stnictures as indicators of device state, function, operation, mode, or othcr conditions or characteristics.
Examples of indicators include "wheel" or rotating structures such as dials or buttons that, when turned to a given position, indicate a particular function, mode, or statc of band 220. Other structurcs may include single or multiple-position switches that, when turned to a given position.
arc also configured for the uscr to visually recognize a function, mode, or state of band 220. For example, a 4-position switch or button may indicate "on," "off," standby,"
"active," "inactive,"
or other mode. A 2-position switch or button may also indicate other modes of operation such as "on" and "off." As yet anothcr example, a single switch or button may be provided such that, when the switch or button is depressed, band 220 changes mode or function without.
alternatively, providing a visual indication. In othcr examples, different types of buttons, switches, or other uscr interfaces may bc provided and arc not limited to the examples shown.

FIG. 3 illustrates sensors for use with an exemplary data-capable strapband.
Sensor 212 may bc implemented using various types of sensors, sonic of which arc shown.
Like-numbered and named elements may describe the same or substantially similar clement as those shown in other descriptions. Here, scnsor 212 (FIG. 2) may be implemented as accelerometer 302, altimeter/barometer 304, light/infrared ("IR") scnsor 306, pulse/heart rate ("HR") monitor 308, audio sensor (e.g., microphone, transducer, or others) 310, pedometer 312, velocimeter 314, GPS receiver 316, location-baSed service sensor (e.g., sensor for determining location within a cellular or micro-cellular network, which may or may not use GPS or other satellite constellations for fixing a position) 318, motion detection scnsor 320, environmental sensor 322, chemical scnsor 324, electrical sensor 326, or mechanical sensor 328.
As shown, accelerometer 302 may bc used to capture data associated with motion detection along I, 2, or 3-axes of measurement, without limitation to any specific type of specification of sensor. Accelerometer 302 may also bc implemented to measure various types of user motion and may be configured based on the type of sensor, firmware, software, hardware, or circuitry used. As another example. altimeter/barometer 304 may be used to measure environment pressure, atmospheric or otherwise, and is not limited to any specification or type of pressure-reading device. In some examples, altimeter/barometer 304 may be an altimeter, a barometer, or a combination thereof. For example, altimeter/barometer 304 may be implemented as an altimeter for measuring above ground level ("AGL") pressure in band 200.
which has been configured for use by naval or military aviators. As another example, altimeter/barometer 304 may bc implemented as a barometer for reading atmospheric pressure for marine-based applications. In other examples, altimeter/barometer 304 may be implemented differently.
Other types of sensors that may bc uscd to measure light or photonic conditions include light/IR sensor 306, motion detection sensor 32(), and environmental sensor 322. the latter of which may include any type of sensor for capturing data associated with environmental conditions beyond light. Further, motion detection sensor 320 may be configured to detect motion using a variety of techniques and technologies, including, but not limited to comparative or differential light analysis (e.g., comparing foreground and background lighting), sound monitoring, or others. Audio scnsor 310 may bc implemented using any type of device configured to record or capture sound.
In some examples, pedometer 312 may bc implemented using devices to measure various typcs of data associated with pedestrian-oriented activities such as running or walking.
Footstrikes, stridc length, stride length or interval, time, and other data may be measured.
Velocimetcr 314 may bc implemented, in some examples, to measure velocity (e.g., speed and directional vectors) without limitation to any particular activity. Further, additional scnsors that may be used as scnsor 212 include those configured to identify or obtain location-based data.
For example, GPS receiver 316 may be used to obtain coordinates of thc geographic location of band 200 using, for example, various types of signals transmitted by civilian and/or military satellite constellations in low, medium, or high earth orbit (e.g., "LEO,"
"MEO," or "GEO-). In othcr examples, differential GPS algorithms may also be implemented with GPS
receiver 316, which may be used to generate more precise or accurate coordinates. Still further. location-based services sensor 318 may bc implemented to obtain location-based data including, but not limited to location, nearby services or items of interest, and thc likc. As an example, location-based services scnsor 318 may be configured to detect an electronic signal, encoded or otherwise, that provides information regarding a physical locale as band 200 passcs. The electronic signal may include, in some examples, encoded data regarding thc location and information associated therewith. Electrical sensor 326 and mechanical sensor 328 may bc configured to include othcr types (e.g., haptic, kinctic, piezoelectric, piczomechanical, pressure, touch, thermal, and others) of sensors for data input to band 200, without limitation. Other types of sensors apart from those shown may also be used, including magnetic flux sensors such as solid-state compasses and the like. The scnsors can also include gyroscopic sensors. While the present illustration provides numerous examples of types of sensors that [nay he used with band 200 (FIG. 2), others not shown or described may be implemented with or as a substitute for any sensor shown or described.
FIG. 4 illustrates an application architecture for an exemplary data-capable strapband.
Here, application architecture 400 includes bus 402, logic module 404, communications module 406, sccurity module 408, interface module 410, data management 412, audio module 414, motor controller 416, service management module 418, sensor input evaluation module 420, and power management module 422. In some examples, application architecture 400 and the above-listed elements (e.g., bus 402, logic module 404, communications module 406, security module 408, interface module 410, data management 412, audio module 414, motor controller 416, service management modttic 418, sensor input evaluation module 420, and power management module 422) may be implemented as software using various computer programming and formatting languages such as Java, C++, C, and others. As shown here, logic module 404 may bc firmware or application software that is installed in memory 206 (FIG. 2) and executed by proccssor 204 (FIG. 2). Included with logic module 404 may be program instructions or code (e.g., source, object, binary executables, or others) that, whcn initiated, called, or instantiated, perform various functions.
For example, logic module 404 may be configured to scnd control signals to communications module 406 in order to transfer, transmit, or receive data stored in memory 206, the latter of which may be managed by a database management system ("DBMS") or utility in data management module 412. As another example, security module 408 may be controlled by logic module 404 to provide encoding, decoding, cncryption, authentication, or other functions to band 200 (FIG. 2). Alternatively, security module 408 may also be implemented as an application that, using data captured from various scnsors and stored in mcmory 206 (and accessed by data management module 412) may be used to provide identification functions that enable band 200 to passively idcntify a user or wearer of band 200. Still further, various types of security software and applications may be used and are not limited to thosc shown and described.
Interface module 410, in some examples, may be uscd to manage uscr interface controls such as switches, buttons, or othcr typcs of controls that enable a uscr to tnanagc various functions of band 200. For example, a 4-position switch may be turned to a given position that is interpreted by interface module 410 to determine the proper signal or feedback to send to logic module 404 in order to generate a particular result. In other examples.
a button (not shown) may bc depressed that allows a user to trigger or initiate certain actions by sending another signal to logic module 404. Still further, interface module 410 may be used to interpret data from, for example, accelerometer 210 (FIG. 2) to identify specific movement or motion that initiates or triggers a given response. In othcr examples, interface module 410 may be used to manage different types of displays (e.g., light-emitting diodes (LEDs), interferometric modulator display (MOD), electrophoretic ink (E Ink), organic light-cmitting diode (OLED), etc.). In othcr examples, interface module 410 may be implemented differently in function, structure, or configuration and is not limited to those shown and described.
As shown, audio module 414 may be configured to manage encoded or unencodcd data gathered from various types of audio sensors. In some examples, audio module 414 may include one or morc codecs that are used to encode or dccodc various types of audio waveforms. For example, analog audio input may be encoded by audio module 414 and, once encoded, sent as a signal or collection of data packcts, messages, segments, frames, or the like to logic module 404 for transmission via communications module 406. In other examples, audio module 414 may be implemented differently in function, structure, configuration, or implementation and is not limited to those shown and described. Other elements that may bc uscd by band 200 include motor controller 416, which may be firmware or an application to control a motor or other vibratory energy source (e.g., vibration source 208 (FIG. 2)). Power used for band 200 may bc drawn from battery 214 (FIG. 2) and managed by powcr management module 422, which may be firmware or an application used to manage, with or without user input, how powcr is consumer, conserved, or otherwise used by band 200 and the above-dcscribed elements, including one or more sensors (e.g., sensor 212 (FIG. 2), sensors 302-328 (FIG. 3)). With regard to data captured, scnsor input evaluation module 420 may be a software engine or module that is used to evaluate and analyze data received from one or more inputs (e.g., sensors 302-=328) to band 200. When received, data may be analyzed by sensor input evaluation module 420, which may include custom or "off-the-shelf' analytics packages that arc configured to provide application-spccific analysis of data to determine trcnds, patterns, and other useful information.
In other examples, sensor input module 420 may also include firmware or softwarc that enables thc generation of various types and formats of rcports for presenting data and any analysis performed thereupon.
Another clement of application architecture 400 that may be included is service management module 418. In some examples, service management module 418 may bc firmware, software, or an application that is configured to manage various aspects and operations associated with executing software-related instructions for band 200. For example, libraries or classes that arc used by software or applications on band 200 may bc served from an online or networked sourcc. Service management module 418 may be implemented to manage how and when these services are invoked in order to ensure that desired applications are executed properly within application architecture 400. As discrctc sets, collections, or groupings of functions, services used by band 200 for various purposes ranging from communications to operating systems to call or document libraries may bc managed by service management module 418. Alternatively, service management module 418 may be implemented differently and is not limited to the examples provided herein. Further, application architecture 400 is an example of a software/system/application-level architecture that may be used to implement various software-related aspects of band 200 and may bc varied in the quantity, type, configuration, function.
structure, or typc of programining or formatting languages used, without limitation to any given example.
FIG. 5A illustrates representative data types for use with an exemplary data-capable strapband. Here, wearable device 502 may capture various types of !data, including, but not limited to scnsor data 504, manually-entered data 506, application data 508, location data 510, network data 512, system/operating data 514, and user data 516. Various types of data may be captured from sensors, such as those described above in connection with FIG.
3. Manually-entered data, in some examples, may be data or inputs received directly and locally by band 200 (FIG. 2). In other examples, manually-entered data may also be provided through a third-party website that storcs the data in a database and may be synchronized from server 114 (FIG. 1) with one or more of bands 104-112. Other types of data that may be captured including application data 508 and system/operating data 514, which may be associated with firmware, software, or hardware installed or implemented on band 200. Further, location data 510 may be used by wearable device 502, as described above. User data 516, in some examples, inay be data that include profile data, preferences, rules, or other inforination that has bccn previously entered by a given uscr of wearable device 502. Further, network data 512 may be data is captured by wearable device with regard to routing tables, data paths, network or access availability (e.g., wireless network access availability), and thc like. Other types of data may bc captured by wearable device 502 and arc not limited to the examples shown and described.
Additional context-specific examples of types of data captured by bands (04-112 (FIG. I) arc provided below. =
FIG. 5B illustrates representative data typcs for usc with an exemplary data-capable strapband in fitncss-rclatcd activities. Here, band 519 may be config,urcd to capture types (i.c., categories) of data such as heart ratc/pulse monitoring data 520, blood oxygen saturation data 522, skin temperature data 524, salinity/emission/outgassing data 526, location/GPS data 528, environmental data 530, and accelerometer data 532. As an example, a runner may use or wear band 519 to obtain data associated with his physiological condition (i.e., heart rate/pulse monitoring data 520, skin temperature, salinity/emissionfoutgassing data 526, among others), athletic efficiency (i.e., blood oxygen saturation data 522), and performance (i.c., location/GPS
data 528 (e.g., distance or laps run), environmental data 530 (e.g., ambient temperature, humidity, pressure, and thc like), accelerometer 532 (e.g., biomcchanical information, including gait, stride, stride length, among others)). Other or different typcs of data may bc captured by band 519, but the above-described examples are illustrative of some types of data that may bc capturcd by band 519. Further, data capturcd may bc uploaded to a website or online/networked destination for storage and other uses. For example, fimess-related data may be used by applications that are downloaded from a "fitness marketplace" where athletes may find, purchase, or download applications for various uses. Some applications may be activity-specific and thus may he used to modify or alter the data capture capabilities of band 519 accordingly.
For example, a fitness marketplace may be a website accessible by various types of mobile and non-mobile clients to locate applications for different exercise or Fitness categories such as running, swimming, tennis, golf, baseball, football, fencing, and many others.
When downloaded, a fitness marketplace may also be used with user-specific accounts to manage the retrieved applications as well as usage with band 519, or to use thc data to provide services such as online personal coaching or targeted advertisements. More, fewer, or different types of data may be captured for fitness-related activities.
FIG, 5C. illustrates represcntatiVe data types for use with an exemplary data-capable strapband in sleep management activities. Here, band 539 may be used for sleep management purposcs to track various typcs of data. including heart rate monitoring data 540, motion sensor data 542, accelerometer data 544, skin resistivity data 546, user input data 548, clock data 550, and audio data 552. In somc examples, heart rate monitor data 540 may bc captured to evaluate rest, waking, or various states of sleep. Motion sensor data 542 and accelerometer data 544 may bc used to &tern-line whether a user of band 539 is experiencing a restful or fitful sleep. For example, some motion scnsor data 542 may be capturcd by a light sensor that measures ambient or differential light patterns in ordcr to detemine whether a user is sleeping on hcr front, side, or back. Accelerometer data 544 may also be captured to determine whether a user is experiencing gentle or violent disruptions when sleeping, such as thosc oftcn found in afflictions of sleep apnea or othcr sleep disorders. Further, skin resistivity data 546 may bc captured to determine whether a user is ill (e.g., running a temperature, sweating, experiencing chills, clammy. skin, and others). Still further, user input data may include data input by a user as to how and whether band 539 should trigger vibration source 208 (FIG. 2) to wake a uscr at a given time or whcthcr to use a scrics of increasing or decreasing vibrations to trigger a waking state. Clock data (550) may be used to measure the duration of sleep or a finite period of time in which a user is at rest.
Audio data may also bc captured to determine whcthcr a uscr is snoring and, if so, thc frequencies and amplitude therein may suggest physical conditions that a user may be interested in knowing (e.g., snoring, breathing interruptions, talking in one's sleep, and the like). More, fewer, or different types of data may bc captured for sleep management-related activities.
FIG. 5D illustrates representative data types for use with an exemplary data-capable strapband in tnedical-related activities. Here, band 539 may also be configured for medical purposes and related-types of data such as heart rate monitoring data 560, respiratory monitoring data 562, body temperature data 564, blood sugar data 566, chemical protein/analysis data 568, patient medical records data 570, and healthcare professional (e.g., doctor, physician, registered nursc, physician's assistant, dcntist, orthopcdist, surgeon, and others) data 572. In sonic examples, data may be captured by band 539 directly from wear by auser. For example, band 539 may be able to sample and analyze sweat through a salinity or moisture detector to idcntify whether any particular chemicals, protcins, hormones, or othcr organic or inorganic compounds arc present, which can be analyzed by band 539 or communicated to server 114 to perform further analysis. If sent to server 114, further analyses may be perfornied by a hospital or other medical facility using data captured by band 539. In other examples, more, fewer, or different types of data may be captured for medical-related activities.
FIG. 5E illustrates representative data types for use with an exemplary data-capable strapband in social media/networking-related activities. Examples of social media/networking-related activities include related to Internet-based Social Networking 15 Services ("SNS"), such as Facebook , Twitter , etc. Here, band 519, shown with an audio data plug, may bc configured to capture data for use with various types of social media and networking-related services, websitcs, and activities. Accelerometer data 580, manual data 582, othcr user/friends data 584, location data 586, network data 588, clock/timer data 590, and environmental data 592 are examples of data that may bc gathered and sharcd by, for example, uploading data from band 519 using, for example, an audio plug such as those described herein. As another example, accelerometer data 580 may bc captured and shared with other users to share motion, activity, or other movement-oriented data. Manual data 582 may be data that a given user also wishes to share with other users. Likewise, other uscr/fricnds data 584 may bc from other bands (not shown) that can bc shared or aggregated with data captured by band 519.
Location data 586 for band 519 may also be shared with other users. In other examples, a user may also enter manual data 582 to prevent other users or friends from receiving updated location data from band 519.
Additionally, nctwork data 588 and clock/timer data may be captured and shared with other users to indicate, for example, activities or events that a given user (i.c., wearing band 519) was engaged at certain locations. Further, if a uscr of band 519 has friends who arc not geographically located in close or near proximity (e.g., thc user of band 519 is located in San Francisco and hcr friend is located in Rome), environmental data can bc capturcd by band 519 (e.g., weather, temperature, humidity, sunny or overcast (as interpreted from data captured by a light scnsor and combined with captured data for humidity and temperature), among others). In other examples, more, fcwcr, or different typcs of data may bc captured for inedical-related activities.
FIG. 6 illustrates a transition between modes of operation for a strapband in accordance with various embodiments. A strapband can transition between modes by either entering a mode at 602 or exiting a mode at 660. Thc flow to enter a mode begins at 602 and flows downward, whereas the flow to exit the mode begins at 660 and flows upward. A mode can be entered and exited explicitly 603 or entered and exited implicitly 605. In particular, a uscr can indicate explicitly whether to cntcr or cxit a mode of operation by using inputs 620.
Examples of inputs 620 include a switch with onc or more positions that arc each associated with a selectable mode, and a display 1/0 624 that can be touch-sensitive for entering commands explicitly to enter or exit a mode. Note that entry of a second mode of operation can extinguish implicitly the first mode of operation. Further, a uscr can explicitly indicate whether to enter or exit a mode of operation by using motion signatures 610. That is, the motion of the strapband can facilitate transitions between modes of operation. A motion signature is a set of motions or patterns of motion that the strapband can detect using the logic of the strapband, whereby the logic can infer a mode from the motion signature. Examples of motion signatures are discussed below in FIG.
1 l. A set of motions can be predctennined, and then can be associated with a command to enter or exit a mode. Thus, motion can select a mode of operation. In some embodiments, modes of operation include a "normal" modc, an "active mode," a "sleep mode" or "resting modes"), among other types of modes. A normal mode includes usual or normative amount of activities, whereas, an "active mode" typically includes relatively large amounts of activity, Active mode can include activities, such as running and swimming, for example. A "sleep mode" or "resting mode" typically includes a relatively low amount of activity that is indicative of sleeping or resting can be indicative of the user sleeping.
A mode can bc entered and exited implicitly 605. In particular, a strapband and its logic can determine whcthcr to enter or cxit a mode of operation by inferring either an activity or a mode at 630. An inferred mode of operation can be determined as a function of user characteristics 632, such as detdrmined by user-relevant sensors (e.g., heart rate, body temperature, etc.). An inferred mode of operation can bc determined using motion matching 634 (e.g., motion is analyzed and a type of activity is determined). Further, an inferred mode of operation can be determined by examining environmental factors 636 (e.g., ambient temperature, time, ambient light, etc.). To illustrate, consider that: (I.) user characteristics 632 specify that the user's heart rate is at a resting rate and the body temperature falls (indicative of resting or sleeping), (2.) motion matching 634 determines that thc uscr has a relatively low level of activity, and (3.) environment factors 636 indicatc that the time is 3:00 am and thc ambient light is negligible. In view of thc foregoing, an inference engine or othcr logic of thc strapband likely can infer that the user is sleeping and then operate to transition the strapband into sleep mode. In this mode, power may be reduced. Note that while a mode may transition cithcr explicitly or implicitly, it need not exit the same way.
FIG. 7A illustrates a perspective view of an exemplaty data-capable strapband configured to receive overmolding. Here, band 700 includes framework 702, covering 704, flexible circuit 706, covering 708, motor 710, coverings 714-724, plug 726, accessory 728, control housing 734, control 736, and flexible circuits 737-738. In some exatnples, band 700 is shown with various elements (i.e., covering 704, flexible circuit 706, covering 708, motor 710, coverings 714-724, plug 726, accessory 728, control housing 734, control 736, and flexible 1() circuits 737-738) coupled to framework 702. Coverings 708, 714-724 and control housing 734 may bc configured to protect various typcs of elements, which may be electrical, electronic, mechanical, structural, or of another typc, without litnitation. For example, covering 708 may bc used to protcct a battery and power management module from protective material formed around band 700 during an injection molding operation. As another example, housing 704 may be used to protect a printed circuit board assembly ("PCBA") from similar damage. Further, control housing 734 may be used to protect various types of user interfaces (e.g., switches, buttons (e.g., control 736), lights, light-emitting diodes, or other control features and functionality) from damage. In other exainples, the elements shown may be varied in quantity, type, manufacturer, specification, function, structure, or other aspects in order to provide data capture, communication, analysis, usage, and other capabilities to band 700, which may be worn by a user around a wrist, arm, leg, ankle, neck or other protnision or aperture, without restriction. Band 700, in some examples, illustrates an initial unlaycred device that may be protected using the techniques for protective overmolding as described above.
Alternatively, the number, type, function, configuration, ornamental appearance, or other aspects shown may bc varied without limitation.
FIG. 7B illustrates a side view of an exemplary data-capable strapband. Here, band 740 includes framework 702, covering 704, flexible circuit 706, covering 708, motor 710, battery 712, coverings 714-724, plug 726, accessory 728, button/switch/LED/LCD Display 730-732, control housing 734, control 736, and flexible circuits 737-738 and is shown as a side viel.v band 700. In othcr examples, the number, typc, function, configuration, ornamental appearance, or other aspects shown may bc varied without limitation.
FIG. 7C illustrates another side view of an exemplary data-capable strapband.
Here, band 750 includes framework 702, covering 704, flexible circuit 706, covering 708, motor 710, battery 712, coverings 714-724, acccssory 728. button/switch/LED/LCD Display 730-732, control housing 734, control 736, and flexible circuits 737-738 and is shown as an opposite side view of band 740. In some examples, button/switch/LED/LCD Display 730-732 may bc implemented using different types of switches, including multiple position switchcs that may bc manually tumed to indicatc a given function or command. Furthcr, undcrlighting provided by light emitting diodes ("LED") or other types of low power lights or lighting ystems may be used to provide a visual status for band 750. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 7D illustrates a top view of an exemplary data-capable strapband. Here, band 760 includes framework 702, coverings 714-716 and 722-724, plug 726, accessory 728, control housing 734, control 736, flexible circuits 737-738, and PCBA 762. In other examples, thc number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 7E illustrates a bottom view of an exemplary data-capable strapband.
Here, band 770 includes framework 702, covering 704, flexible circuit 706, covering 708, motor 710, coverings 714-720, plug 726, accessory 728, control housing 734, control 736, and PCBA 772.
In some examples, PCBA 772 may be implemented as any type of electrical or electronic circuit board clement or component, without restriction. In other examples, thc number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 7F illustrates a front view of an exemplary data-capable strapband. Here, band 780 includes framework 702, flexible circuit 706, covering 708, motor 710, coverings 714-718 and 722, accessory 728, button/switch/LED/LCD Display 730, control housing 734, control 736, and flexible circuit 737. In some examples, button/switch/LED/LCD Display 730 may bc implemented using various types of displays including liquid crystal (LCD), thin film, active matrix, and others, without limitation. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 70 illustrates a rear view of an exemplary data-capable strapband. Here, band 790 includes framework 7()2, covering 708, motor 71(), coverings 714-722, analog audio plug 726, accessory 728, control 736, and flexible circuit 737. In some examples, control 736 may be a button configured for depression in ordcr to activate or initiatc other functionality of band 790.
In other examples, the number, type, function, configuration, ornamental appearance, or other aspccts shown may bc varied without limitation.
FIG. 8A illustrates a perspective of an exemplary data-capable strapband having a first molding. Here, an alternative band (i.e., band 800) inclUdes molding 802, analog audio TRRS-type plug (hereafter "plug") 804, plug housing 806, button 808, framework 810, control housing 812, and indicator light 814. In some examples, a first protective ovcrmolding (i.c., molding 802) has been applied over band 700 (FIG. 7) and thc above-described .clements (e.g., covering 704, flexible circuit 706, covering 708, motor 710, coverings 714-724, plug 726, accessory 728, control housing 734, control 736, and flexible circuit 738) !caving some elements partially exposed (e.g., plug 804, plug housing 806, button 808, framework 810, control housing 812, and indicator light 814). However, internal PCBAs, flexible connectors, circuitry, and other sensitive elements have been protectively covered with a first or inncr molding that can bc configured to furthcr protcct band 800 from subsequent moldings formed over band 800 using the above-described techniques. In other examples, the type, configuration, location. shape, design, layout, or other aspects of band 800 may be varied and arc not limited to those shown and described. For example, TRRS plug 804 may be removed if a wireless communication facility is instead attached to framework 810, thus having a transceiver, logic, and antenna instead being protected by molding 802. As another example, button 808 may bc removed and replaced by another control mechanism (e.g., an accelerometer that provides motion data to a processor that, using firmware and/or an application, can idcntify and resolve different types of motion that band 800 is undergoing), thus enabling molding 802 to be extended more fully, if not completely, over band 800. In other examples, the number, type, function, configuration, ornamental appearance, or other aspccts shown may be varied without limitation.
FIG. 8B illustrates a sidc view of an exemplary data-capable strapband. Here, band 820 includes molding 802, plug 804, plug housing 806, button 808, control housing 812, and indicator lights 814 and 822. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 8C illustrates another side view of an exemplary data-capable strapband.
Here, band 825 includes molding 802, plug 804, button 808, framework 810, control housing 812, and indicator lights 814 and 822. The view shown is an opposite view of that presented in FIG. 8B.
In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 8D illustrates a top view of an exemplary data-capable strapband. Here, band 830 includes molding 802, plug 804, plug housing 806, button 808, control housing 812, and indicator lights 814 and 822. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 8E illustrates a bottom view of an exemplary data-capable strapband.
Here, band 840 includes molding 802, plug 804, plug housing 806, button 808, control housing 812, and indicator lights 814 and 822. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 8F illustrates a front view of an exemplary data-capable strapband. Here, band 850 includes molding 802, plug 804, plug housing 806, button 808, control housing 812, and indicator light 814. In other examples, thc number, type, function, configuration, ornainental appearance, or othcr aspects shown may be varied without limitation.
FIG. 8G illustrates a rear view of an exemplary data-capable strapband. Hcrc, band 860 includes molding 802 and button 808. In other examples, the numbcr, type, function, configuration, ornamental appearance, or other aspccts shown may be varied without limitation.
-FIG. 9A illustrates a perspective view of an exemplary data-capable strapband having a second inolding. Here, band 900 includes molding 902, plug 904, and button 906. As shown another ovennolding or protective material has been formed by injection molding, for example, molding 902 over band 900. As another molding or covering layer, molding 902 inay also be configured to receive surface designs, raised textures, or patterns, which may be uscd to add to thc commercial appeal of band 900. In some examples, band 900 may bc illustrative of a finished data-capable strapband (i.e., band 700 (FIG. 7), 800 (FIG. 8) or 900) that may bc configured to provide a widc range of electrical, electronic, mechanical, structural, photonic, or =
other capabilities.
Here, band 900 may be configured to perforin data communication with one or more othcr data-capablc devices (e.g., other bands, computers, networked computers, clients, servers, peers, and thc like) using wired or wireless features. For example, plug 900 may be used, in connection with firmware and software that allow for the transmission of audio tones to send or receive encoded data, which may be performed using a variety of encoded waveforms and protocols, without limitation. In othcr examples, plug 904 may bc removed and instead replaced with a wireless communication facility that is protected by molding 902. If using a wireless coinmunication facility and protocol, band 900 may communicate with other data-capable devices such as cell phoncs, smart phones, computers (e.g., desktop, laptop, notebook, tablet, and the like), computing networks and clouds, and other types of data-capable devices, without limitation. In still other examples, band 900 and the elements described above in connection with FIGs. 1-9, may be varied in type, configuration, function, structure, or other aspects, without limitation to any of the exainples shown and described.
FIG. 9B illustrates a side view of an exemplary data-capable strapband. Here, band 910 includes molding 902, plug 904, and button 906. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
=
FIG. 9C illustrates another side view of an exemplary data-capable strapband.
Here, band 920 includes molding 902 and button 906. In other examples, the number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 9D illustrates a top view of an exemplary data-capable strapband. Here, band 930 includes molding 902, plug 904, button 906, and textures 932-934. In some examples, textures 932-934 may be applied to the external surface of molding 902. As an example, textured surfaces may be molded into thc cxtcrior surface of molding 902 to aid with handling or to provide ornamental or aesthetic designs. The type, shape, and repetitive nature of textures 932-934 arc not limiting and designs may be either two or three-dimensional relative to the planar surface of molding 902. In other examples, the number, type, function, configuration, ornamental appearance, or othcr aspects shown may be varied without limitation.
FIG. 9E illustrates a bottom view of an exemplary data-capablc strapband.
Here, band 940 includes molding 902 and textures 932-934, as dcscribcd above. In other examples, the number, typc, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 9F illustrates a front view of an exemplary data-capable strapband. Hcrc, band 950 includes molding 902, plug 904, and tcxturcs 932-934. In other examples, thc number, type, function, configuration, ornamental appearance, or other aspects shown may be varied without limitation.
FIG. 9G illustrates a rcar view of an exemplary data-capablc strapband. Here, band 960 includes molding 902, button 906, and textures 932-934. In other examples, the number, type, function, configuration, ornamental appearance, or othcr aspects shown may bc varied without limitation.
FIG. 10 illustrates an exemplary computer system suitable for usc with a data-capable strapband. In some examples, computer system 1000 may bc used to. implement computer programs, applications, methods, processes, or other software to perform thc above-described techniques. Coinputer system 1000 includes a bus 1002 or other communication mechanism for comtnunicating information, which intcrconnccts subsystems and devices, such as processor 1004, system memory 1006 (e.g., RAM), storage device 1008 (e.g., ROM), disk drive 1010 (e.g., magnetic or optical), communication interface 1012 (e.g., modem or Ethernet card), display 1014 (e.g., CRT or LCD), input device 1016 (e.g., keyboard), and cursor control 1018 (e.g., mouse or trackball).
According to sonic examples, computer system 1000 perfornis specific operations by processor 1004 executing one or more sequences of one or more instructions stored in system memory 1006. Such instructions tnay be read into system memory 1006 from another computer readable medium, such as static storage device 1008 or disk drive 1010. In some examples, hard-wired circuitry may bc used in place of or in combination with software instructions for iinplementation.
The tent "computer readable medium" refers to any tangible medium that participates in providing instructions to processor 1004 for execution. Such a medium may take many forms, including but not limited to, non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as disk drive 1010.
Volatile media includes dynamic memory, such as system memory 1006.
Common forms of computer readable media includes, for example, floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM. any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, RAM, PROM, EPROM, FLASH-EPROM, any other memory chip or cartridge, or any other medium from which a computer can read.
Instructions may furthcr bc transmitted or received using a transmission medium. The term "transmission medium" may include any tangible or intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such instructions. Transmission media includes coaxial cables, copper wire, and fibcr optics, including wires that comprise bus 1002 for transmitting a computer data signal.
In some examples, execution of thc sequences of instructions may bc performed by a single computer system 1000. According to some examples, two or more computer systems 1000 coupled by communication link 1020 (e.g., LAN, PSTN, or wireless network) may perform the sequence of instructions in coordination with onc another.
Computer system 1 MO
may transmit and receive messages, data, and instructions, including program, i.e., application code, through communication link 1020 and communication interface 1012.
Received program codc may bc cxccutcd by processor 1004 as it is received, and/or stored in disk drive 1010, or othcr non-volatile storage for later execution.
FIG. 11 depicts a variety of inputs in a specific example of a strapband, such as a data-, capable strapband, according to various embodiments. In diagram 1100, strapband 1102 can include one or more of the following: a switch 1104, a display 1/0 1120, and a multi-pole or multi-position switch 1101. Switch 1 1()4 can rotate in dircction 1107 to select a mode, or switch 1104 can be a push button operable by pushing in direction 1105, whereby subsequent pressing of the button cycles through different modes of operation. Or, different sequences of short and long durations during which the button is activated. Display I/0 1120 can be a touch-sensitive graphical user interface. The multi-pole switch 1 101, in some examples, can be a four-position switch, each position being associated with a mode (e.g., a sleep mode, an active mode, a normal mode, etc.). Additionally, commands can be entered via graphical user interface 1112 via wireless (or wired) communication device 1110. Further, any number of visual outputs (e.g..
LEDs as indicator lights), audio outputs, and/or mechanical (e.g., vibration) outputs can be itnplemented to inform the user of an event, a mode, or any other status of interest relating to the functionality of the strapband.
FIGs. 12A to I 2F depict a variety of motion signatures as input into a strapband, such as a data-capable strapband, according to various embodiments. In FIG. 12A, diagram 1200 dcpicts a user's arm (e.g., as a locomotive member or appendage) with a strapband 1202 attached to uscr wrist 1203. Strapband 1202 can envelop or substantially surround uscr wrist 1203 as well. FIGs. I 2B to 12D illustrate different "motion signatures"
defined by various ranges of motion and/or motion patterns (as well as number of motions), whereby each of thc motion signatures identifies a mode of operation. FIG. I 2B dcpicts up-and-down motion, FIG.
I2C depicts rotation abut the wrist, and FIG. 12D depicts sidc-to-sidc motion, FIG. 12E
depicts an ability detect a change in mode as a function of thc motion and deceleration (e.g..
when a user claps hands or makes contact with a surfacc 1220 to gct strapband to change modes), whereas, FIG. 12F dcpicts an ability to detect "no motion" initially and experience an abrupt acceleration of the strapband (e.g., uscr taps strapband with finger 1230 to change modes). Note that motion signatures can be motion patterns that arc predetermined. with the user selecting or linking a specific motion signature to invoke a specific mode. Note, too, a user can define unique motion signatures. In some embodiments, any numbcr of detect motions can be used to define a motion signature. Thus, different numbcrs of thc same motion can activate different modcs. For example, two up-and-down motions in FIG. 12B can activate onc mode, whereas four up-and-down motions can activate another modc. Further, any combination of motions (e.g., two up-and-down motions of FIG. 12B and two taps of FIG. 12E) can bc uscd as an input, regardless whether a mode of operation or otherwise.
FIG. 13 depicts an inference engine of a strapband configured to detect an activity and/or a mode bascd on monitored motion, according to various embodiments. In some einbodiments, inference engine 1304 of a strapband can be Configured to detect an activity or mode, or a state of a strapband, as a function of at least data derived from one or morc sourccs of data, such as any number of sensors. Examples of data obtained by the sensors include, but arc not limited to, data describing motion, location, user characteristics (e.g., heart rate, body temperature, ctc.), environmental characteristics (e.g., time, degree of ambient light, altitude, magnetic flux (e.g., magnetic field of the earth), or any othcr sourcc of magnetic flux), GPS-gencrated position data, proximity to other strapband wearers, etc.), and data derived or sensed by any source of relevant information. Further, inference engine 1304 is configured to analyze scts of data from a variety of inputs and sources of infonnation to identify an activity, mode and/or state of a strapband. In one example, a set of sensor data can include (3PS-derived data, data representing magnetic flux, data representing rotation (e.g., as derived by a gyroscope). and any other data that can be relevant to inference engine 1304 in its operation. The inference engine can use positional data along with motion-related information to identify an activity or mode, among other imposes.
According to sonic embodiments, inference engine 1304 can be configured to analyze real-time sensor data, such as user-related data l 301 derived in real-time from sensors and/or environmental-related data 1303 derived in rcal-time from sensors. In particular, inference engine 1304 can compare any of the data derived in real-time (or from storage) against othcr = types of data (regardless of whether the data is real-time or archived).
The data can originate from different sensors, and can obtained in real-time or from memory as user data 1352.
Therefore, inference engine 1304 can be configured to compare data (or sets of data) against each other, thereby matching sensor data, as well as other data, to determine an activity or mode.
Diagram 1300 depicts an example of an inference engine 1304 that is configured to determine an activity in which the user is engaged, as a ftinction of motion and, in some embodiments, as a function of sensor data, such as user-related data 1301 derived from scnsors and/or environmental-related data 1303 derived from sensors. Examples of activities that inference engine 1304 evaluates include sitting, sleeping, working, running, walking, playing soccer or baseball, swimming, resting, socializing, touring, visiting various locations, shopping at a storc, and the likc. These activities arc associated with different motions of thc user, and, in particular, different.motions of one or more locomotive members (e.g., motion of a uscr's arm or wrist) that are inherent in thc different activities. For example, a user's wrist motion during running is more "pendulum-like" in it motion pattern, whereas, thc wrist motion during swimming (e.g., freestyle strokcs) is more "circular-like" in its motion pattern. Diagram 1300 also dcpicts a motion matcher 1320, which is configured to dctcct and analyze motion to determine the activity (or the most probable activity) in which the user is engaged. To further refine the determination of the activity, inference engine 1304 includes a uscr characterizer 1310 and an environmental detector 1311 to detect sensor data for purposes of comparing subsets of sensor data (e.g., one or more types of data) against other subsets of data.
Upon determining a match between sensor data, inference engine 1304 can use the matched sensor data, as well as motion-related data, to idcntify a specific activity or mode. User characterizer 1310 is configured to accept user-related data 1301 from relevant sensors. Examples of uscr-related data 1301 include heart rate, body temperature, or any other personally-relatcd information with which inference engine 1304 can determine, for example, whether a uscr is sleeping or not.
Further, environmental detector 1311 is configured to acccpt environmental-related data 1303 from rclevarit scnsors. Examples of environmental-related data 1303 include timc, ambicnt temperature, degree of brightness (e.g., whether in the dark or in sunlight), location data (e.g., GPS data, or derived from wireless nctworks), or any other environmental-related information with which inference engine 1304 can determine whether a user is engaged in a particular activity.
A strapband can opcmtc in different modes of operation. One mode of operation is an "active mode." Active mode can bc associated with activities that involve relatively high degrees of motion at relatively high rates of change. Thus, a strapband enters thc active mode to sufficiently capture and monitor data with such activities, with power consumption as being less critical. In this mode, a controller, such as mode controller 1302, operates at a higher sample rate to capture the motion of the strapband at, for example, higher rates of speed. Certain safety or health-related monitoring can be implemented in active mode, or, in response to engaging in a specific activity. For example, a controller of strapband can monitor a user's heart rate against normal and abnormal heart rates to alert the user to any issues during, for example, a strenuous activity. In some embodiments, stmpband can bc configured as set forth in FIG.
5B and uscr charactcrizer 1310 can process user-related information from sensors described in relation FIG.
5B. Another mode of operation is a "sleep mode." Sleep mode can bc associated with activities that involve relatively low degrees of motion at relatively low rates of change. Thus, a strapband cntcrs thc sleep mode to sufficiently capture and monitor data with such activities, while preserving power. In sonic embodiments, strapband can bc configured as sct forth in FIG.
5C and user chamcterizer 1310 can process user-related information from sensors described in relation FIG. 5C. Yet another modc is "normal mode," in which the strapband operates in accordance with typical uscr activities, such as during work, travel, movement around the house, bathing, ctc. A strapband can operate in any number different modes, including a health monitoring mode, which can implement, for example, the features set forth in FIG. 5D. Another mode of operation is a "social mode" of operation in which thc uscr interacts with other users of similar strapbands or communication devices, and, thus, a strapband can implement, for example, thc features sct forth in FIG. 5E. Any of these modes can bc entered or exited either explicitly or implicitly.
Diagram 1300 also dcpicts a motion matcher 1320, which is confiL,Tured to detect and analyze motion to determine thc activity (or thc most probable activity) in which the user is engaged. In various embodiments, motion matcher 1320 can fonn part of inference cnginc 1304 (not shown), or can have a structurc and/or function separate therefrom (as shown). Regardless, the structures and/or functions of inference engine 1304, including tiscr characterizer 1310 and an environmental detector 1311, and motion matcher 1320 cooperate to determine an activity in which the user is engaged and transmit data indicating the activity (and other related information) to a controller (e.g., a mode controller 1302) that is configured to control operation of a mode, such as an "active mode," of the strapband.
Motion matcher 1320 of FIG. 13 includes a motion/activity deduction engine 1324, a motion capture manager 1322 and a motion analyzer 1326. Motion matcher 1320 can receive motion-rclated data 1303 from relevant sensors, including those sensors that relate to spacc or position and to time. Examples of such scnsors include accelerometers, motion detectors.
velociineters, altimeters, barometers, etc. Motion capture manager 1322 is configured to capture portions of motion, and to aggregate those portions of motion to form an aggregated motion pattern or profile. Further, motion capture manager 1322 is configured to store motion patterns as profiles 1344 in database 1340 for real-time or future analysis. Motion profiles 1344 include sets of data relating to instances of motion or aggregated portions of motion (e.g., as a function of time and space, such as expressed in X, Y, Z coordinate systems).
For example, motion capture manager 1322 can be configured to capture motion relating to the activity of walking and motion relating to running, each motion being associated with a specific profile 1344. To illustrate, consider that motion profiles 1344 of walking and running share some portions of motion in common. For example, the user's wrist motion during running and walking share a "pendulum-like" pattern over time, but differ in sampled positions of the strapband. During walking, the wrist and strapband is generally at waist-level as the user walks with arms relaxed (e.g., swinging of thc arms during walking can result in a longer arc-like motion pattern over distancc and time), whereas during running, a uscr typically raises the wrists and changes the orientation of the strapband (e.g., swinging of thc arms during running can result in a shorter arc-likc motion pattern). Motion/activity deduction engine 1324 is configured to access profiles 1344 and dcducc, for. example, in rcal-timc whether the activity is walking or running.
Motion/activity deduCtion engine 1324 is configured to analyze a portion of motion and deduce the activity (e.g., as an aggregate of the portions of motion) in which thc uscr is engaged and provide that information to the inference engine 1304, which, in turn, compares user characteristics and environmental characteristics against thc dcduccd activity to confirm or reject the dctcrmination. For example, if motion/activity dcduction engine 1324 deduces that monitorcd motion indicates that thc uscr is sleeping, thcn thc heart rate of thc uscr, as a uscr characteristic, can be used to compare against thresholds in user data 1352 of database 1350 to confirm that the uscr's heart rate is consistent with a sleeping user. Uscr data 1352 can also include past location data, whereby historic location data can bc used to determine whether a location is frequented by a user (e.g., as a means of identifying the user).
Furthcr, inference engine 1304 can evaluate environmental characteristics, such as whether there is ambient light (e.g., darkness implies conditions for resting), the titne of day (e.g., a person's sleeping times typically can bc between 12 midnight and 6 am), or other related information.
In operation, motion/activity deduction engine 1324 can be configured to store motion-related data to form motion profiles 1344 in real-time (or near real-time). In some embodiments, the motion-related data can be compared against motion reference data 1346 to determine "a match" of motions. Motion rcfcrcncc data 1346, which includes reference motion profiles and patterns, can be derived by motion data captured for the user during previous activities, whereby the previous activities and motion thereof serve as a reference against which to compare. Or, motion reference data 1346 can include ideal or statistically-rcicvant tnotion pattcrns against which motion/activity deduction engine 1324 determines a match by determining which reference profile data 1346 "bcst fits" the real-time motion data.
Motion/activity deduction engine 1324 can operate to determine a motion pattern, and, thus, determine an activity. Notc that motion reference profile data 1346, in some embodiments, serves as a "motion fingerprint"
for a user and can be unique and personal to a specific user. Therefore, motion reference profile data 1346 can be used by a controller to determine whether subsequent use of a strapband is by the authorized user or whether the current user's real-time motion data is a mismatch against motion reference profile data 1346. If there is mismatch, a controller can activate a security protocol responsive to thc unauthorized use to preserve information or generate an alert to be communicated external to thc strapband.
Motion analyzer 1326 is configured to analyze motion, for example, in real-timc, among other things. For example, if the uscr is swinging a baseball bat or golf club (e.g., when the strapband is located on the wrist) or the uscr is kicking a socccr ball (e.g., when the strapband is located on thc ankle), motion analyzer 1326 evaluates thc captured motion to detect, for example, a deceleration in motion (e.g., as a motion-centric event), which can be indicative of an impulse event, such as striking an object, like a golf ball. Motion-related characteristics, such as space and time, as well as othcr environment and uscr charactcristics can be captured relating to the motion-centric event. A motion-centric event, for example, is an event that can relate to changes in position during motion, as well as changes in timc or velocity. In some embodiments, inference engine 1304 storcs user charactcristic data and environmental data in database 1350 as user data 1352 for archival purposes, reporting purposes, or any other purpose.
Similarly inference engine 1304 and/or motion matcher 1320 can store motion-related data as motion data 1342 for rcal-timc and/or futurc usc. According to some embodiments, storcd data can bc accessed by a user or any cntity (e.g., a third party) to adjust the data of databases 1340 and 1350 to, for example, optimize motion profile data or sensor data to ensure more accurate results. A uscr can access motion profile data in database 1350. Or, a uscr can adjust the functionality of infcrcncc engine 1304 to ensure more accurate or prccisc determinations. For example, if inference engine 1304 detects a user's walking motion as a running motion, the user can modify the behavior of the logic in the strapband to increase tile accuracy and optimizc die operation of the strapband.
FIG. 14 dcpicts a representative implementation of onc or more strapbands and equivalent devices, as wearable devices, to form unique motion profiles, according to various embodiments. In diagram 1400, strapbands and an equivalent device are disposcd on locomotive members of the user, whereby the locomotive members facilitate motion relative to and about a ccntcr point 1430 (e.g., a reference point for a position, such a a center of mass). A
headset 1410 is configured to communicate with strapbands 1411, 1412, 1413 and 1414 and is disposcd on a body portion 1402 (e.g., tile head), which is subject to motion relative to center point 1430. Strapbands 1411 and 1412 arc disposed on locomotive portions 1404 of the user (e.g., the arms or wrists), whereas strapbands 1413 and 1414 are disposed on locomotive portion 1406 of the user (e.g., the legs or ankles). As shown, headset 1410 is disposed at distance 1420 from center point 1430, strapbands 1411 and 1412 arc disposed at distance 1422 from center point 1430, and strapbands 1413 and 1414 are disposed at distance 1424 from center point 1430.
A great number of users have different values of distances 1420, 1422, and 1424. Further, different wrist-to-elbow and elbow-to-shoulder lengths for different users affect the relative motion of strapbands 1411 and 1412 about center point 1430, and similarly, different hip-to-knee and knee-to-ankle lengths for different users affect the relative motion of strapbands 1413 and 1414 about center point 1430. Moreover, a great number of users have unique gaits and styles of motion. Thc above-described factors, as well as other factors, facilitate the determination of a unique motion profile for a uscr per activity (or in combination of a number of activities). The uniqueness of the motion patterns in which a user performs an activity enables thc usc of motion profile data to provide a "motion fingerprint." A
"motion fingerprint"
is unique to a uscr and can be compared against detected motion profiles to determine. for example, whether a usc of thc strapband by a subsequent wearer is unauthorized. In some cases, unauthorized users do not typically share common motion profiles. Note that while four arc shown, fcwcr than four can be uscd to establish a "motion fingerprint," or more can be shown (e.g., a strapband can be disposed in a pocket or otherwise carried by the user). For example, a user can place a single strapbands at different portions of the body to capture motion patterns for those body parts in a serial fashion. Then, each of the motions patterns can be combined to form a "motion fingerprint." In some cascs, a single strapband 1411 is sufficient to establish a "motion fingerprint." Notc, too, that onc or more of strapbands 1411, 1412, 1413 and 1414 can bc configured to operate with multiple users, including non-human users, such as pets.
FIG. 15 dcpicts an example of a motion capture manager configured to capturc motion and portions therefore, according to various embodiments. Diagram 1500 depicts an example of a motion matcher 1560 and/or a motion capturc manager 1561, onc or both of which arc configured to capture motion of an activity or statc of a uscr and generate onc or more motion profiles, such as motion profile 1502 and motion profile 1552. Database 1570 is configured to store motion profiles 1502 and 1552. Note that motion profiles 1502 and 1552 arc shown as graphical representation of motion data for purposes of discussion, and can bc stored in any suitable data structure or arrangement. Note, too, that motion profiles 1502 and 1552 can represent real-timc motion data with which a motion matcher 1560 uses to determine modes and activities.
To illustrate operation of motion capture manager 1561, consider that motion profile 1502 reprcsents motion data capturcd for a running or walking activity. Thc data of motion profile 1502 indicates the user is traversing along the Y-axis with motions describable in X, Y, Z
coordinatcs or any other coordinate system. The rate at which motion is capturcd along the Y-axis is based on the sampling rate and includes a time component. For a strapband disposed on a wrist of a user, motion capture manager 1561 captures portions of motion, such as repeated motion segments A-to-B and B-to-C. In particular, motion capturc manager 1561 is configured to detect motion. for an arm 1501a in the +Y direction from the beginning of the forward swinging anri (e.g., point A) to the end of the forward swinging arm (e.g., point B). Further, motion capture rnanager 1561 is configured to detect motion for arm 150lb in the -Y direction from thc beginning of the backward swinging arm (e.g., point B) to the cnd of thc backward swinging arm (e.g., point C). Note that point C is at a greater distance along the Y-axis than point A as the center point or center mass of the user has advanced in the +Y
direction. Motion capture manager 1561 continues to monitor and capture motion until, for example, motion capturc manager 1561 detects no significant motion (i.c., below a threshold) or an activity or modc is ended.
Note that in some embodiments,. a motion profile can be captured by motion capture manager 1561 in a "nonrial mode" of operation and sampled at a first sampling rate ("sample rate 1") 1532 bctwccn samples of data 1520, which is a relatively slow sampling rate that is . configured to operate with normal activities. Samples of data 1520 represent not only motion data (e.g., data regarding X, Y, and Z coordinatcs, time, accelerations, velocities, etc.), but can also represent or link to user related information capturcd at those sample times. Motion matcher 1560 analyzes the motion, and, if thc motion relates to an activity associated with an "active mode," motion matcher 1560 signals to the controller, such as a mode controller, to change modes (e.g., from normal to active mode). During active mode, thc sampling rate increases to a sccond sampling rate ("sample rate 2") 1534 between samples of data 1520 (e.g., as well as between a sample of data 1520 and a sample of data 1540). An increased sampling rate can facilitate, for example, a more accurate sct of captured motion data.
To illustrate the above, considcr that a uscr is sitting or strctching prior to a work out. Thc user's activities likely are occurring in a normal mode of operation. But once motion data of profile 1502 is detected, a motion/activity deduction engine can deduce the activity of running, and then can infer the mode ought to be the active modc. The logic of the strapband then can place the strapband into the active mode. Therefore, the strapband can change modes of operation implicitly (i.e., explicit actions to change modes need not be necessary). In some cases, a mode controller can identify an activity as a "running" activity, and then invoke activity-specific functions, such as an indication (e.g., a vibratory indication) to the user every one-quarter mile or 15 minute duration during the activity.
FIG. 15 also dcpicts anothcr motion profile 1552. Consider that motion profile represents motion data captured for swimming activity (e.g., using a freestyle stroke). Similar to profile 1502, thc motion pattern data of motion profile 1552 indicates thc uscr is traversing along the Y-axis. The rate at which motion is captured along the Y-axis is based on the sampling ratc of samples 1520 and 1540, for example. For a strapband disposed on a wrist of a uscr, motion capture manager 1561 captures the portions of motion, such as motion segments A-to-B and B-to-C. In particular, motion capture manager 1561 is configured to detect motion for an ann 1551a in the direction from thc beginning of a forward arc (e.g., point A) to the end of the forward arc (e.g., point B). Further, motion capturc manager 1561 is configured to detect motion for arm 1551b in the -Y direction from the beginning of reverse arc (e.g., point B) to the end of the reverse arc (e.g., point C). Motion capture manager 1561 continues to monitor and capture motion until, for example, motion capture manager 1561 detects no significant motion (i.e., below a threshold) or an activity or mode is ended.
In operation, a mode controller can determine that the motion data of profile 1552 is associated with an active mode, similar with the above-described running activity, and can place the strapband into the active mode, if it is not already in that mode.
Further, motion matcher 1560 can analyze thc motion pattern data of profile 1552 against, for example, thc motion data of profile 1502 and conclude that the activity associated with the data being captured for profile 1552 docs not relate to a running activity. Motion matcher 1560 then can analyze profile 1552 of the real-time generated motion data, and, if it determines a match with reference motion data for the activity of swimming, motion matcher 1560 can generate an indication that thc user is performing "swimming" as an activity. Thus, the strapband and its logic can implicitly determine an activity that a user is performing (i.c., explicit actions to specify an activity need not be ncccssary). Therefore, a mode controller then can invoke swimming-specific functions, such as an application to generate an indication (e.g., a vibratory indication) to the uscr at completion of every lap, or can count a number of strokes. While not shown, motion matcher 1560 and/or a motion capture manager 1561 can bc configured to implicitly determine modes of operation, such as a sleeping modc of operation (e.g., the mode controller, in part, can analyze motion patterns against a motion profile that includes sleep-rclated motion data. Motion matcher 1560 and/or a motion capturc manaucr 1561 also can bc configured to an activity out of a number of possible activities.
FIG. 16 depicts an example of a motion analyzer configured to evaluate motion-ccntric events, according to various embodiments. Diagram 1600 depicts an exainple of a motion matcher 1660 and/or a motion analyzer 1666 for capturing motion of an activity or state of a user and generating one or more motion profiles, such as a motion profile 1602. To illustrate, consider that motion profile 1602 represents motion data captured for an activity of swinging a baseball bat 1604. The motion pattern data of motion profile 1602 indicates thc user begins thc swing at position 1604a in the -Y direction. The user moves thc strapband and the bat to position 1604b, and then swings the bat toward the -Y direction when contact is made with the baseball at position 1604c. Note that the sct of data samples 1630 includes data samples 1630a and 1630b at relatively close proximity to each othcr in profile 1602. This indicatcs a deceleration (e.g., a slight, but detectable deceleration) in the bat when it hits the baseball. Thus, motion analyzer 1666 can analyze motion to determine motion-centric events, such as striking a baseball, striking a golf ball, or kicking a soccer ball. Data regarding the motion-centric events can be stored in database 1670 for additional analysis or archiving purposes, for exainple.
FIG. 17 illustrates action and event processing during a mode of operation in accordance with various embodiments. At 1702, the strapband enters a mode of operation.
During a certain mode, a controller (e.g., a mode controller) can be configured to monitor user characteristics at 1704 relevant to the mode, as well as relevant motion at I 706 and environmental factors at 1708.
The logic of the strapband can operate to detect user and mode-related events at 1710, as well as motion-centric events at 1712. Optionally, upon detection of an event, thc logic of thc strapband can perfortn an action at 1714 or inhibit an action at 1716, and continue to loop at 1718 during the activity or mode.
To illustrate action and event processing of a strapband, considcr the following examples. First, consider a person is perforining an activity of running or _jogging, and enters an active mode at 1702. The logic of the strapband analyzes uscr characteristics at 1704, such as sleep patterns, and determines that the person has been getting less than a normal amount of sleep for the last fcw days, and that the person's heart ratc indicates thc user is undergoing strenuous exercise as confirmed by detected motion in 1706. Further, the logic determines a large number of wireless signals. indicating a populated arca, such as along a busy street. Next, the logic detects an incoming call to the user's headset at I 71(). Given the state of thc user, the logic suppresses the call at 1716 to ensure that thc user is not distracted and thus not endangered.
As a second example, considcr a person is performing an activity of sleeping and has entered a sleep mode at 1702. The logic of the strapband analyzes user characteristics at 1704, such as heart rate, body temperature, and othcr user characteristics relevant to the determination whether the person is in REM sleep. Further, the person's motion has decreased sufficiently to match that typical of periods of deep or REM sleep as confirmed by detected motion (or lack thereof) at 1706. Environmental factors indicate a relatively dark room at 1708. Upon determination that the user is in REM sleep, as an event, at 1710, the logic of the strapband inhibits an alarm at 1716 set to wake the user until REM sleep is over. This process loops at 1718 until the user is out of REM sleep, when the alarm can be performed subsequently at 1714.
In onc example, the alarm is implemented as a vibration generated by the strapband. Note that the strapband can inhibit the alarrn features of a mobile phone, as the strapband can communicate an alarm disable signal to thc mobile phone.
In at least sotric examples, the structures and/or functions of any of the above-described features can be implemented in software, hardware, firmware, circuitry, or a combination thereof. Notc that the structures and constituent elements above, as well as thcir functionality, niay bc aggregated with onc or more othcr structures or elements.
Alternatively, the elements and their functionality may be subdividcd into constitucnt sub-cicments, if any. As software, the above-described techniques may bc implemented using various types of programming or formatting languages, frameworks, syntax, applications, protocols, objects, or techniques. As hardware and/or firmware, thc above-described techniques may bc implemented using various types of programming or integrated circuit design languages, including hardWare description languages, such as any register transfcr language ("RTL") configured to design ficld-= programmable gate arrays ("FPGAs"), application-specific integrated circuits (-ASICs"), or any other type of integrated circuit. These can be varied and are not limited to the examples or descriptions provided.
FIG. 18A illustrates an exemplary wearable device for sensory user interface.
Here, a cross-sectional view of wearable device 1800 includes housing 1802, switch 1804, switch rod I 806, switch scal 1808, pivot arm 1810, spring 1812, printed circuit board (hereafter "PCB") 1814, support 1816, light pipes 1818-1820, and light windows 1822-1824. In some examples, wearable device 1800 may bc implemented as part of band 900 (FIG. 9A), providing a user interface for a uscr to interact, manage, or otherwise tnanipulatc controls for a data-capable strapband. As shown, when switch 1804 is depressed and stopped by switch seal 1808, switch rod 1806 may bc configured to mechanically engage pivot arm 1810 and causc electrical contact with one or more elements on PCB 1814. In an alternative example, pivot arm 1810 may cause light to be selectively reflected back, depending on the position of pivot arm 1810, to PCB 1814, which may coinprise an optical transmitter/receiver to detect the reflection and to report back different rotational positions of pivot arm 1810. In another alternative example, pivot arm 1810 may comprise magnets, which may bc brought into, and out of, proximity with onc or more magnetic field sensor on PCB 1814 indicating different rotational positions of switch 1804. In other examples, switch 1804 may be configured to rotate and causc electrical contact with other elements on PCB 1814. Spring 1812 is configured to return switch rod 1806 and button 1804 to a recoiled position to await another user input (e.g., depression of switch 1804). In some exaMples, light sourccs (e.g., LED 224 (FIG. 2A)) tnay be mounted on PCB 1814 and, using light pipes 1818 and 1820 provide illuminated displays through light windows (822 and 1824.

Further, light windows 1822 and 1824 may be implemented as rotating switches that arc translucent, transparent, or opaque and, when rotatcd, emit light from different features that visually indicatc when a different function, mode, or operation is present. In other examples, wearable device 1800 may be implemented differently and is not limited to those provided.
FIG. 18B illustrates an alternative exemplary wearable device for sensory user interface.
Here, a cross-sectional view of an alternative wearable device 1830 includes switch rod 1806, pivot arm 1810, spring 1812. light pipcs 1818-1820. switch seal 1832, and dctents 1834. In some examples, switch seal 1832 may be configured differently than as shown in FIG.
18A, providing a flush surfacc against which switch 1804 (FIG. 18A) may bc depressed until stopped by detents 1834. Further, switch seal 1832 may bc formed using material that is waterproof, water-resistant, or otherwise able to prevent thc intrusion of undesired materials, chemicals, or liquids into the interior cavity of wearable device 1830. In other examples, wearable device 1830 may bc configured, designed, formed, fabricated, function, or otherwise implemented differently and is not limited to the fcaturcs, functions, and structures shown.
FIG. I 8C illustrates an exemplary switch rod to be used with an exemplary wearable device. Here, a perspective view of switch rod 1806, which may bc configured to act as a shaft or piston that, when depressed using switch 1804 (FIG. 18A), engages pivot atm 1810 (FIG.
18A) and moves into electrical contact one or more components on PCB 1814.
Limits on the rotation or movement of switch rod 1806 may be provided by various types of mechanical structures and arc not limited to any examples shown and described.
FIG. I 8D illustrates an exemplary switch for use with an exemplary wearable device.
Here, a distal end of wearable device 1840 is shown including housing 1802, switch 1804, and concentric scal 1842. As an alternative design, concentric seal 1842 may be implemented to provide greater connectivity between switch 1804 and detcnts 1834 (not shown;
FIG. 18B). As shown, a concentric well in concentric seal 1842 may be configured to receive switch 1804 and, when depressed, engage switch rod 1806 (not shown; FIG. I 8A). In other examples, wearable device 1840 and the .above-described elements may be varied in function, structurc, design, implementation, or other aspects and are not limited to those shown.
FIG. 18E illustrates an exemplary sensory user interface. Here, wearable device 1850 includes housing 1802, switch 1804, and light windows 1822-1824. In some examples, light windows 1822-1824 may be implemented using various designs, shapes, or features in ordcr to permit light to emanate from, for example, LEDs mounted on PCB 1814. Furthcr, light windows 1822-1824 may also bc implemented as rotating switches that, when turned to a given orientation, provide a visual indication of a function, mode, activity, state, or operation being performed. In other examples, wearable device 1850 and the above-described elements may be implemented differently in design, function, or structure, and arc not limited to those shown.
Although thc foregoing examples have bccn described in some detail for purposes of clarity of understanding, thc above-dcseribcd inventive techniques arc not limited to the details provided. There are many alternative ways of' implementing the above-described invention techniques. The disclosed examples are illustrative and not restrictive.

Claims (22)

What is claimed:

1. A method, comprising:
receiving a sensory input at a sensor coupled to a wearable device;
converting the sensory input into data using the sensor and the processor;
processing the data to generate a representation of a state;
evaluating the representation to determine if an action is indicated; and performing the action if indicated based on an evaluation of the representation.

2. The method of claim 1, wherein the sensory input is a temperature.

3. The method of claim 1, wherein the sensory input is a measure of galvanic skin response.

4. The method of claim 1, wherein the sensory input is evaluated by the processor to determine a caloric burn rate.

5. The method of claim 1, wherein the sensory input is a clock signal.

6. The method of claim 1, wherein the sensory input is a signal used to determine a location.

7. The method of claim 1, wherein receiving the sensory input further comprises taking one or more temperature measurements, the one or more temperature measurements being evaluated to determine a Circadian rhythm.

8. The method of claim 1, wherein performing the action further comprises monitoring body temperature.

9. The method of claim 1, wherein performing the action further comprises generating an alert configured to modify a cognitive behavior.

10. The method of claim 1, wherein processing the data further comprises determining skin conductance response.

11. The method of claim 10, further comprising using the skin conductance response to determine whether to generate an alert.

12. The method of claim 1, wherein processing the data to generate the representation further comprises determining whether the representation is within a range of tolerance.

13. The method of claim 1, wherein the state is determined by an activity.

14. The method of claim 1, wherein the state is biological.

15. The method of claim 1, wherein the state is physiological.

16. The method of claim 1, wherein the state is psychological.

17. The method of claim 1, wherein performing the action further comprises generating an alert if the state has changed.

18. The method of claim 1, wherein the alert is initiated on a headset in wireless communication with the wearable device.

19. A sensory user interface system, comprising:
a wearable device being in data communication with a sensor configured to detect an input;

a memory configured to store data associated with the input and the wearable device: and a processor configured to receive the input by the sensor, to convert the input into the data using the sensor and the processor, to process the data to generate a representation of a state, to evaluate the representation to determine if an action is indicated, and to perform the action if indicated based on an evaluation of the representation.

20. The sensory user interface system of claim 19, wherein the processor is coupled to the wearable device and configured to generate and to evaluate the representation.

21. The sensory user interface system of claim 19, wherein the processor is in data communication with the wearable device and configured to generate and to evaluate the representation.

22. A computer program product embodied in a computer readable medium and comprising computer instructions for:
receiving a sensory input at a sensor coupled to a wearable device;
converting the sensory input into data using the sensor and the processor;
processing the data to generate a representation of a state;
evaluating the representation to determine if an action is indicated; and performing the action if indicated based on an evaluation of the representation.