Comparison of the specification of ‘S46 patent as filed to the specification of the
`
`‘D38 patent as filed.
`
`65 of 173
`
`65 of 173
`
`

`
`TITLE
`
`SYSTEM FOR MONITORING AND
`
`
`
`CROSS REFERENCE TO RELATED APPLICATIONS
`
`This application is a continuation in part of—United States Application Serial
`
`
`
`5
`
`I0
`
`I5
`
`FIELD OF THE INVENTION
`
`The present invention relates to a=sysrem-é
`
`fitness. C particular,E toE to an=
`
`20
`
`66 of 173
`
`66 of 173
`
`

`
`BACKGROUND OF THE INVENTION
`
`Research has shown that a large number of the top health problems in society are either
`
`caused in whole or in part by an unhealthy lifestyle. More and more, our society requires people to
`
`lead fast-paced, achievement-oriented lifestyles that often result in poor eating habits, high stress
`
`levels, lack of exercise, poor sleep habits and the inability to find the time to center the mind and
`
`are becoming increasingly interested in establishing a healthier lifestyle-
`
`I0
`
`Traditional medicine, embodied in the form of an HMO or simila— does not
`
`have the time, the training, or the reimbursement mechanism to address the needs of those
`
`individuals interested in a healthier lifestyle. There have been several attempts to meet the needs of
`
`these individuals, including a perfusion of fitness programs and exercise equipment, dietary plans,
`
`self-help books, altemative therapies, and most recently, a plethora of health information web sites
`
`15
`
`on the lntemet. Each of these atternptsnargeted to empower the individual to take charge and get
`
`healthy. Each ofthese attempts, however, addresses only part ofthe -needs of individuals seeking a
`
`healthier lifestyle and ignores many of the real barriers that most individuals face when trying to
`
`adopt a healthier lifestyle. These barriers include the fact that the individual is often left to himself
`
`or herself to find motivation, to implement a plan for achieving a healthier lifestyle, to monitor
`
`20
`
`progress, and to brainstorm solutions when problems arise; the fact that existing programs are
`
`directed to only certain aspects of a healthier lifestyle, and rarely come as a complete package; and
`
`the fact that recommendations are often not targeted to-the unique characteristics ofthe individual or
`
`his life circumstances.
`
`, 67 of173
`
`67 of 173
`
`

`
`With respect to weight loss, specifically, many medical and other commercial methodologies
`
`have been developed to assist
`
`individuals in losing excess body weight and maintaining an
`
`appropriate weight level through various diet, exercise and behavioral modification techniques.
`
`Weight Watchers is an example of a weight loss behavior modification system in which an
`
`individual manages weight loss with a points system utilizing commercially available foods; All
`
`food items are assigned a certain number ofpoi nts based on serving size and content of fat, fiber and
`
`calories. Foods that are high in fat are assigned a higher number of points. Foods that are high in
`
`fiber receive a lower number of points. Healthier foods are typically assigned a lower number of
`
`points, so the user is encouraged to eat these food items.
`
`l0
`
`A user is assigned a daily points range which represents the total amount of food the user
`
`should consume within each day. Instead of directing the user away from a list of forbidden foods, a
`
`auser is encouraged to enjoy all foods in moderation, as long as they fit withina user's points budget.
`
`The program is based on calorie reduction, portion control and modification ofcurrent cating habits.
`
`Exercise activities are also assigned points which are subtracted from the points accumulated by a
`
`I5
`
`user's daily calorie intake.
`
`Weight Watchers attempts to make a user create a balance of exercise and healthy eating in
`
`their life. However, because only caloric value of food is specifically tracked, the program tends to
`
`fail in teaching the user about the nutritional changes they need to make to maintain weight loss.
`
`Calorie content is not the only measurement that a user should take into control when determining
`
`20
`
`what food items to consume. Items that contain the same caloric content may not be nutritiously
`
`similar. So, instead ofdeveloping healthy eating habits, a user might become dependent on counting
`
`points. It is important to note that the Weight Watchers program deals essentially with caloric intake
`
`only and not caloric expenditure.
`
`68 of 173
`
`Lg)
`
`68 of 173
`
`

`
`Similarly, Jenny Craig is also a weight loss program. Typically, an individual is assigned a
`
`personal consultant who monitors weight loss progress. In addition, the individual will receive pre-
`
`selected menus which are based on the Food Guide Pyramid for balanced nutrition. The menus
`
`contain Jenny Craig branded food items which are shipped to the individual's home or any other
`
`location chosen by the individual. The Jenny Craig program teaches portion control because the
`
`food items to be consumed are pre—portioned and supplied by Jenny Craig. However, such a close
`
`dietary supervision can be a problem once the diet ends because the diet plan does not teach new
`
`eating habits or the value of exercise. Instead it focuses mainly on short term weight loss goals.
`
`The integration of computer and diet tracking systems has created several new and more
`
`automated approaches to weight
`
`loss. Available methodologies can be tailored to meet the
`
`individuals specific physiological characteristics and weight loss goals.
`
`BalanceLog, developed by HealtheTech, Inc. and the subject of United States Published
`
`Application No. 20020133378 is a software program that provides a system for daily tracking and
`
`monitoring of caloric intake and expenditure.
`
`The user customizes the program based on
`
`metabolism in addition to weight and nutrition goals. The user is able to create both exercise and
`
`nutrition plans in addition to tracking progress. However, the BalanceLog system has several
`
`10
`
`IS
`
`limitations.
`
`First, a user must know their resting metabolic rate, which is the number ofcalories burned at
`
`rest. The user can measure their resting metabolic rate. However, a more accurate rate can be
`
`20
`
`measured by appointment at a metabolism measurement location. Atypical individual, especially
`
`an individual who is beginning a weight and nutrition management plan may view this requirement
`
`as an inconvenience. The system can provide an estimated resting metabolic rate based on a broad
`
`population average if a more accurate measurement cannot be made. However, the resting metabolic
`
`69 of 173
`
`69 of 173
`
`

`
`rate can vary widely between individuals having similar physiological characteristics. Thus, an
`
`estimation may not be accurate and would affect future projections of an individual's progress.
`
`Second, the system is limited by the interactivity and compliance of the user. Every aspect of
`
`the Bal anceLog system is manual. Every item a user cats and every exercise a user does must be
`
`logged in the system.
`
`If a user fails to do this, the reported progress will not be accurate. This
`
`manual data entry required by BalanceLog assumes that the user will be in close proximity to a data
`
`entry device, such as a personal digital assistant or a personal computer, to enter daily activities and
`
`consumed meals. However, a user may not consistently or reliably be near their data entry device
`
`shortly thereafter engaging in an exercise or eating activity. They may be performing the exercise
`
`activity at a fitness center or otherwise away from such a device. Similarly, a user may not be eating
`
`a certain meal at home, so they may not be able to log the information immediately after consuming
`
`the meal. Therefore, a user must maintain a record of all food consumed and activities performed so
`
`that these items can be entered into the BalanceLog system at a later time.
`
`Also, the BalanceLog system does not provide for the possibility ofestimation. A user must
`
`select the food consumed and the corresponding portion size of the food item. If a time lapse has
`
`occurred between the meal and the time of entry and the user does not remember the meal, the data
`
`may not be entered accurately and the system vvould suffer from a lack of accuracy. Similarly, ifa
`
`user does not remember the details of an exercise activity, the data may not be correct.
`
`Finally,
`
`the BalanceLog system calculates energy expenditure based only upon the
`
`information entered by the user. A user may only log an exercise activity such as running on a
`
`treadmill for thirty minutes for a particular day. This logging process does not take into account the
`
`actual energy expenditure of the individual, but instead relies on averages or look-up tables based
`
`upon general population data, which may not be particularly accurate for any specific individual.
`
`[0
`
`15
`
`20
`
`70 of 173
`
`70 of 173
`
`

`
`The program also ignores the daily activities of the user such as walking up stairs or running to catch
`
`the bus. These dailyactivities need to be taken into account for a user to accurately determine their
`
`total amount of energy expenditure.
`
`Similarly FitDay, a sofiware product developed by Cyser Software, is another system that
`
`allows a user to track both nutrition and exercise activity to plan weight loss and monitor progress.
`
`The FitDay software aids a user in controlling diet through the input of food items consumed. This
`
`software also tracks the exercise activity and caloric expenditure through the manual data entry by
`
`the user. The FitDay software also enables the user to track and graph body measurements for
`
`additional motivation to engage in exercise activity. Also, FitDay also focuses on another aspect of
`
`weight loss. The system prompts a user for information regarding daily emotions for analysis ofthe
`
`triggers that may affect a user's weight loss progress.
`
`FitDay suffers from the same limitations of Balance Log. FitDay is dependent upon user
`
`input for its calculations and weight loss progress analysis. As a result, the information may sufier
`
`from a lack ofaccuracy or compliance because the user might not enter a meal or an activity. Also,
`
`the analysis of energy expenditure is dependent on the input of the user and does not take the daily
`
`activities of the user into consideration.
`
`Overall, if an individual consumes fewer calories than the number of calories burned, they
`
`user should experience a net weight loss. While the methods described above offer a plurality of
`
`ways to count consumed calories, they do not offer an efficient way to determine the caloric
`
`expenditure. Additionally, they are highly dependent upon compliance with rigorous data entry
`
`requirements. Therefore, what is lacking in the art is a management system that can accurately and
`
`automatically monitor daily activity and energy expenditure of the user to reduce the need for strict
`
`compliance with and the repetitive nature ofmanual data entry of infonnation.
`
`I0
`
`IS
`
`20
`
`71 of173
`
`71 of 173
`
`

`
`SUMMARY OF THE INVENTION
`
`A nutrition and activity management system is disclosed that can help an individual meet
`
`weight loss goals and achieve an optimum energy balance of calories burned versus calories
`
`consumed. The system may be automated and is also adaptable or applicable to measuring a
`
`number of other physiological parameters and reporting the same and derivations of such
`
`parameters. The preferred embodiment, a weight management system, is directed to achieving
`
`an optimum energy balance, which is essential to progressing toward weight loss-specific goals.
`
`I0
`
`Most programs, such as the programs discussed above, offer methods of calorie and food
`
`consumption tracking, but that is only half of the equation. Without an accurate estimation of
`
`energy expenditure, the optimum energy balance cannot be reached.
`
`In other embodiments, the
`
`system may provide additional or substitute information regarding limits on physical activity,
`
`such as for a pregnant or rehabilitating user, or physiological data, such as blood sugar level, for
`
`I5
`
`a diabetic.
`
`The management system that is disclosed provides a more accurate estimation of the total
`
`energy expenditure of the user. The other programs discussed above can only track energy
`
`expenditure through manual input of the user regarding specific physical activity of a certain
`
`duration. The management system utilizes an apparatus on the body that continuously monitors
`
`the heat given off by a user's body in addition to motion, skin temperature and conductivity.
`
`Because the apparatus is continuously worn, data is collected during any physical activity
`
`performed by the user, including exercise activity and daily life activity. The apparatus is
`
`further designed for comfort and convenience so that long term wear is not unreasonable within a
`
`wearer's lifestyle activities.
`
`It is to be specifically noted that the apparatus is designed for both
`
`25
`
`continuous and long term wear. Continuous is intended to mean, however, nearly continuous, as
`
`72 of 173
`
`72 of 173
`
`

`
`the device may be removed for brief periods for hygienic purposes or other de minimus non-use.
`
`Long tenn wear is considered to be for a substantial portion of each day of wear, typically
`
`extending beyond a single day. The data collected by the apparatus is uploaded to the software
`
`platform for determining the number of calories burned, the number of steps taken and the
`
`duration of physical activity.
`
`The management system that is disclosed also provides an easier process for the entry
`
`and tracking of caloric consumption. The tracking of caloric consumption provided by the
`
`management system is based on the recognition that current manual nutrition tracking methods
`
`are too time consuming and difficult to use, which ultimately leads to a low level of compliance,
`
`inaccuracy in data collection and a higher percentage of false caloric intake estimates. Most
`
`users are too busy to log everything they eat for each meal and tend to forget how much they ate.
`
`Therefore, in addition to manual input of consumed food items, the user may select one of
`
`several other methods of caloric input which may include an estimation for a certain meal based
`
`upon an average for that meal, duplication of a previous meal and a quick caloric estimate tool.
`
`A user is guided through the complex task of recalling what they ate in order to increase
`
`compliance and reduce the discrepancy between self-reported and actual caloric intake-
`
`The combination of the information collected from the apparatus and the information
`
`entered by the user is used to provide feedback information regarding the user's progress and
`
`recommendations for reaching dietary goals. Because of the accuracy of the information, the
`
`user can proactively make lifestyle changes to meet weight loss goals, such as adjusting diet or
`
`exercising to burn more calories. The system can also predict data indicative of human
`
`physiological parameters including energy expenditure and caloric intake for any given relevant
`
`time period as well as other detected and derived physiological or contextual information. The
`
`10
`
`I5
`
`20
`
`73 of 173
`
`73 of 173
`
`

`
`
`
`Tincludesgsensor adapted tobe?—
`
`I0
`
`to generate derived data from at least a portion of the data indicative(
`
`
`
`-. at least
`
`is adapted
`
`20
`
`0116 5611501‘.
`
`
`
`74 of 173
`
`74 of 173
`
`

`
`of the sensors is a physiological sensor. The sensors are adapted to generate data indicative of at
`
`least a first parameter of the individual and a second parameter of the individual, wherein the
`
`first parameter is physiological. The apparatus also includes a processor for receiving at _least a
`
`portion of the data indicative of at least a first parameter and a second parameter, the processor
`
`being adapted to generate derived data from the data indicative of at least a first parameter and a
`
`second parameter. The derived data comprises a third parameter of the individual, for example
`
`one selected from the group consisting of ovulation state, sleep state, calories burned, basal
`
`metabolic rate, basal temperature, physical activity level, stress level, relaxation level, oxygen
`
`consumption rate, rise time, time in zone, recovery time, and nutrition activity. The third
`
`parameter is an individual status parameter that cannot be directly detected by any of the at least
`
`two sensors.
`
`In either embodiment of the apparatus, the at least two sensors may be both physiological
`
`sensors, or may be one physiological sensor and one contextual sensor. The apparatus may
`
`further include a housing adapted to be worn on the individual’s body, wherein the housing
`
`supports the sensors or wherein at least one of the sensors _is separately located from the housing.
`
`The apparatus may further include a flexible body supporting the housing having first and
`
`second members that are adapted to wrap around a portion of the individual’s body. The flexible
`
`body may support one or more of the sensors. The apparatus may further include wrapping
`
`means coupled to the housing for maintaining contact between the housing and the individual’s
`
`body, and the wrapping means may support one or more of the sensors.
`
`Either embodiment of the apparatus may further include a central monitoring unit remote
`
`from the at least two sensors that includes a data storage device.‘ The data storage device
`
`receives the derived data from the processor and relrievably stores the derived data therein. The
`
`[0
`
`I5
`
`20
`
`75 of173
`
`10
`
`75 of 173
`
`

`
`apparatus also includes means for transmitting information based on the derived data from the
`
`central monitoring unit to a recipient, which recipient may include the individual or a third party
`
`authorized by the individual. The processor may be supported by a housing adapted to be worn
`
`on the individual’s body, or alternatively may be part of the central monitoring unit.
`
`A weight-loss directed software program is disclosed that automates the tracking of the
`
`energy expenditure of the individual through the use of the apparatus and reduces the repetitive
`
`nature of data entry in the determination of caloric consumption in addition to providing relevant
`
`feedback regarding the user's weight loss goals. The software program is based on the energy
`
`balance equation which has two‘ components: energy intake and energy expenditure. The
`difference between these two values is the energy balance. When this value is negative, a weight
`
`I0
`
`loss should be achieved because fewer calories were consumed than expended. A positive
`
`energy balance will most likely result in no loss of weight or a weight gain.
`
`The weight-loss directed software program may include an energy intake tracking
`
`subsystem, an energy expenditure tracking subsystem, a weight tracking subsystem and an
`
`[5
`
`energy balance and feedback subsystem.
`
`The energy intake tracking subsystem preferably incorporates a food database which
`
`includes an extensive list of commonly consumed foods, common branded foods available at
`
`regional and national food chains, and branded off the shelf entrees and the nutrient information
`
`for each item. The user also has the capability to enter custom preparations or recipes which
`
`20
`
`then become a part of the food in the database.
`
`The energy expenditure subsystem includes a data retrieval process to retrieve the data
`
`from the apparatus. The system uses the data collected by the apparatus to determine total
`
`energy expenditure. The user has the option of manually entering data for an activity engaged in
`
`76 of173
`
`ll
`
`76 of 173
`
`

`
`I0
`
`[5
`
` 0btain life activities data of the individual,-
`
`
`-.
`
`life activities
`
`dam émay also be adapted to generate-E
`
`77 0f173
`
`I2
`
`77 of 173
`
`

`
`_the degree to which-individual has followed a suggested routine. The=
`
` aE'1edatag
`
` the=the life activities data. The central monitoring unit
`
`=adapted to generate and provide feedback to a recipient relating to:
`
`10
`
`IS
`
`78 of 173
`
`78 of 173
`
`

`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`Further features and advantages ofthe present invention will be apparent upon consideration
`
`20
`
`of the following detailed description of the present invention, taken in conjunction with the
`
`'
`
`following drawings, in which like reference characters refer to like parts, and in which:
`
`Fig. l is a diagram of an embodiment of a system for monitoring physiological data
`
`and lifestyle over an electronic network according to the present invention;
`
`Fig. 2 is a block diagram of an embodiment of the sensor device shown in Fig. 1;
`
`79 of173
`
`I4
`
`79 of 173
`
`

`
`Fig. 3 is a block diagram of an embodiment ofthe central monitoring unit shown in
`
`Fig. 1;
`
`Fig. 4 is a block diagram of an aitemate embodiment of the central monitoring unit
`
`shown in Fig. 1;
`
`Fig. 5 is a representation ofa preferred embodiment of the Health Manager web page
`
`according to an aspect of the present invention;
`
`Fig. 6 is a representation of a preferred embodiment of the nutrition web page
`
`according to an aspect of the present invention;
`
`Fig.7
`
`
`
`-is a representation of a preferred embodiment of the activity level web page
`
`according to an aspect of the present invention;
`
`-is a representation of a preferred embodiment ofthe mind centering web page
`
`according to an aspect of the present invention;
`
`-is a representation of a preferred embodiment ofthe sleep web page according
`
`to an aspect of the present invention;
`
`-is a representation ofa preferred embodiment of the daily activities web page
`
`according to an aspect of the present invention;
`
`I0
`
`15
`
`20
`
`80 of 173
`
`15
`
`80 of 173
`
`

`
`-is a representation of a preferred embodiment of the Health Index web page
`
`according to an aspect of the present invention;
`
`-is a from view of a specific embodiment ofthe sensor device shown in Fig. 1;
`
`15
`
`-is a back view ofa specific embodiment ofthe sensor device shown in Fig. I ;
`
`-is a side view ofa specific embodiment ofthe sensor device shown in Fig. 1;
`
`-is a bottom view ofa specific embodiment ofthe sensor device shown in Fig.
`
`Sartre front perspective views ofa specific embodiment of the sensor
`
`20
`
`device shown in Fig. 1;
`
`-is an exploded side perspective view of a specific embodiment ofthe sensor
`
`device shown in Fig. I;
`
`81 of173
`
`I6
`
`81 of 173
`
`

`
`-is a side view of the sensor device shown in Figs.-through-nserted into
`
`a battery recharger unit; and
`
`-is a block diagram illustrating all of the components either mounted on or
`
`coupled to the printed circuit board forming a part of the sensor device shown in Figs.-
`
`through-
`
`I0
`
`15
`
`20
`
`DESCRIPTION OF THE PREFERRED EMBODIMENTS
`
`In general, according to the present invention, data relating to the physiological state, the
`
`lifestyle and certain contextual parameters of an individual is collected and transmitted, either
`
`subsequently or in real-time, to a site, preferably remote from the individual, where it is stored for
`
`later manipulation and presentation to a recipient, preferably over an electronic network such as the
`
`Internet. Contextual parameters as used herein means parameters relating to:the
`
`environment, surroundings and location of the individual, including, but not limited to, air quality,
`
`sound quality, ambient temperature, global positioning and the like- Referring to Fig.1, located at
`
`user location 5 is sensor device 10 adapted to be placed in proximity with at least a portion of the
`
`human body. Sensor device 10 is preferably worn by an individual user on his or her body, for
`
`example as part of a‘ garment such as a form fitting shirt, or as part of an arm band or the like.
`
`Sensor device I 0, includes one or more sensors, which are adapted to generate signals in response to
`
`physiological characteristics of an individual, and a microprocessor. Proximity as used herein means
`
`82 of173
`
`ll?
`
`82 of 173
`
`

`
`that the sensors of sensor device l0 are separated from the individual’s body by a material or the
`
`like, or a distance such that the capabilities of the sensors are not impeded.
`
`Sensor device 10 generates data indicative of various physiological parameters of an
`
`individual, such as the individual '5 heart rate, pulse rate, beat-to-beat heart variability, EKG or
`
`ECG, respiration rate, skin temperature, core body temperature, heat flow offthe body, galvanic skin
`
`response or GSR, EMG, EEG, BOG, blood pressure, body fat, hydration level, activity level, oxygen
`
`consumption, glucose or blood sugar level, body position, pressure on muscles or bones, and UV
`
`radiation exposure and absorption. In certain cases, the data indicative of the various physiological
`
`parameters is the signal or signals themselves generated by the one or more sensors and in certain
`
`other cases the data is calculated by the microprocessor based on the signal or signals generated by
`
`the one or more sensors. Methods for generating data indicative ofvarious physiological parameters
`
`and sensors to be used therefor are vvell known. Table i provides several examples of such well
`
`known methods and shows the parameter in question,—method used,Esensor
`
`device used, and the signal that is generated. Table 1 also provides an indication as to whether
`
`further processing based on the generated signal is required to generate the data.
`
`10
`
`13
`
`Table 1
`
`TM*"-0“E
`zmectrodes
`Dc voltage
`
`Further
`
`Pulse Rate
`
`BVP
`
`LED Emitter and
`Optical Sensor
`
`Change in Resistance
`
`
`
`es
`
`Y
`
`Yes
`
`Beat-to- Beat
`Variability
`
`EKG
`
`DC Voltage
`
`Skin Surface
`Potentials
`
`3- l 0 Electrodes
`
`DC Voltage
`
`83 0f173
`
`18
`
`83 of 173
`
`

`
`TM°"'°"E
`
`Further
`
`
`
`
`
`Respiration Rate
`
`Strain Gauge
`
`Change in Resistance
`
`Skin Temperature
`
`Themiistors
`
`Change in Resistance
`
`
`
`
`Chest Volume
`Change
`
`Surface
`Temperature
`Probe
`
`Core Temperature
`
`Esophageal or
`Rectal Probe
`
`Thermistors
`
`Change in Resistance
`
`Galvanic Skin
`
`Skin Conductance
`
`2 Electrodes
`
`Thermovire
`
`Dc
`
`Response
`
`EMG
`
`EEG
`
`Skin Surface
`Potentials
`
`Skin Surface
`Potentials
`
`Eye Movement
`
`3 Electrodes
`
`DC Voltage
`
`Multiple Electrodes
`
`DC Voltage
`
`
`
`Thin Film
`Piezoelectric
`Sensors
`
`DC Voltage
`
`Blood Pressure
`
`Non-Invasive
`Korotkufl’ Sounds
`
`Electronic
`Sphygromarometer
`
`Change in Resistance
`
`Body Fat
`
`Body Impedance
`
`2 Active Electrodes
`
`Change in Impedance
`
`
`
`Body Movement
`
`
`
`Oxygen
`Consumption
`Glucose Level
`
`Oxygen Uptake
`
`Accelerometer
`
`DC Voltage,
`Capacitance Changes
`
`Electro-chemical
`Electro-chemical
`
`DC Voltage Change
`DC Voltage Change
`
`Yes
`
`Yes
`
`Yes
`
`Yes
`
`No
`
`No
`
`Yes
`
`Yes
`
`Yes
`
`Yes
`
`Yes
`
`Yes
`
`Yes
`
`es
`
`Y
`
`Yes
`
`es
`
`Y
`
`Body Position (e.g.
`supine, erect,
`sitting)
`
`NIA
`
`Mercury Switch
`Array
`
`Muscle Pressure
`
`NFA
`
`DC Voltage Change
`
`DC Voltage Change
`
`Thin Film
`Piezoelectric
`Sensors
`
`
`
`Cells
`
`
`UV Radiation
`Absorption
`
`NIA
`
`UV Sensitive Photo
`
`DC Voltage Change
`
`84 0f173
`
`I9
`
`84 of 173
`
`

`
`
`
`5
`
`10
`
`15
`
`20
`
`The types of data listed in Table l are intended to be examples of the types of data that can
`
`be generated by sensor device 10.
`
`It is to be understood that other types of data relating to other
`
`parameters can be generated by sensor device 10 without departing from the scope of the present
`
`invention.
`
`The microprocessor of sensor device 10 may be programmed to summarize and analyze
`
`the data. For example, the microprocessor can be programmed to calculate an average,
`
`minimum or maximum heart rate or respiration rate over a defined period of time, such as ten
`
`minutes. Sensor device 10 may be able to derive information relating to an individual ' s
`
`physiological state based on the data indicative of one or more physiological parameters. The
`
`microprocessor of sensor device 10 is programmed to derive such information using known
`
`methods based on the data indicative of one or more physiological parameters. Table 2 provides
`
`examples of the type of infonnation that can be derived, and indicates some of the types of data
`
`that can be used therefor.
`
`85 of 173
`
`20
`
`85 of 173
`
`

`
`Derived Information
`
`Sleep onsetfwake
`
`Calories burned
`
`Basal metabolic rate
`
`Table 2
`
`_Data—
`Skin temperature, core temperature, oxygen consumption
`
`Beat-to-beat variability, heart rate, pulse rate, respiration
`rate, skin temperature, core temperature, heat flow, galvanic
`skin response, EMG, EEG, EOG, blood pressure, oxygen
`consumption
`
`Heart rate, pulse rate, respiration rate, heat flow, activity,
`oxygen consumption
`
`Heart rate, pulse rate, respiration rate, heat flow, activity,
`oxygen consumption
`
`Basal temperatu re
`
`Skin temperature, core temperature
`
`Activity level
`
`Stress level
`
`Relaxation level
`
`Heart rate, pulse rate, respiration rate, heat flow, activity,
`oxygen consumption
`
`EKG, beat-to-beat variability, heart rate, pulse rate,
`respiration rate, skin temperature, heat flow, galvanic skin
`response, EMG, EEG, blood pressure, activity, oxygen
`consumption
`
`EKG, beat-to-beat variability, heart rate, pulse rate,
`respiration rate, skin temperature, heat flow, galvanic skin
`response, EMG, EEG, blood pressure, activity, oxygen
`consumption
`
`Maximum oxygen consumption rate
`I
`
`EKG, heart rate, pulse rate, respiration rate, heat flow, blood
`pressure, activity, oxygen consumption
`
`Rise time or the time it takes to rise from
`a resting rate to 85% ofa target maximum
`
`Time in zone or the time heart rate was
`above 85% ofa target maximum
`
`Recovery time or the time it takes heart
`rate to return to a restin g rate after heart
`rate was above 85% ofa target maximum
`
`Heart rate, pulse rate, heat flow, oxygen consumption
`
`Heart rate, pulse rate, heat flow, oxygen consumption
`
`Heart rate, pulse rate, heat flow, oxygen consumption
`
`Additionally, sensor device 10 may also generate data indicative of various contextual
`
`parameters relating to—the environment surrounding the individual. For example,
`
`sensor device I 0 can generate data indicative ofthe air quality, sound levelfquality, light quality or
`
`86 0f173
`
`21
`
`86 of 173
`
`

`
`ambient temperature near the individual, or even the-global positioning of the individual.
`
`Sensor device 10 may include one or more sensors for generating signals in response to contextual
`
`characteristics relating to the environment surrounding the individual, the signals ultimately being
`
`used to generate the type of data described above. Such sensors are well known, as are methods for
`
`generating contextual parametric data such as air quality, sound levelfquality, ambient temperature
`
`and global positioning.
`
`Fig. 2 is a block diagram of an embodiment of sensor device 10. Sensor device 10 includes
`
`at least one sensor 12 and microprocessor 20. Depending upon the nature of the signal generated by
`
`sensor 12, the signal can be sent through one or more of amplifier 14, conditioning circuit 16, and
`
`analog-to-digital converter 18, before being sent to microprocessor 20. For example, where sensor
`
`12 generates an analog signal in need of amplification and filtering, that signal can be sent to
`
`amplifier 14, and then on to conditioning circuit 16, which may, for example, be a band pass filter.
`
`The amplified and conditioned analog signal can then be transferred to analog—to-digital converter
`
`18, where it is converted to a digital signal. The digital signal is then sent to microprocessor 20.
`
`Alternatively,
`
`if sensor 12 generates a digital signal,
`
`that signal can be sent directly to
`
`10
`
`15
`
`microprocessor 20.
`
`A digital signal or signals representing certain physiological andfor contextual characteristics
`
`of the individual user may be used by microprocessor 20 to calculate or generate data indicative of
`
`physiological andlor contextual parameters of the individual user. Microprocessor 20 is
`
`20
`
`programmed to derive information relating to at-one aspect of the individual ' s physiological
`
`state.
`
`It should be understood that microprocessor 20 may also comprise other forms of processors
`
`or processing devices, such as a microcontroller, or any other device that can be programmed to
`
`perform the functionality described herein.
`
`87 of 173
`
`22
`
`87 of 173
`
`

`
`The data indicative of physiological andfor contextual parameters can, according to one
`
`embodiment of the present invention, be sent to memory 22, such as flash memory, where it is stored
`
`until uploaded in the manner to be described below. Although memory 22 is shown in Fig. 2 as a
`
`discrete element, it will be appreciated that it may also be part of microprocessor 20. Sensor device
`
`I0
`
`10 also includes inputfoutput circuitry 24, which is adapted to output and receive as input certain
`
`data signals in the manners to be described herein. Thus, memory 22 of the sensor device 10 will
`
`build up, over time, a store of data relating to the individual user's body and/or environment. That
`
`data is periodically uploaded from sensor device 10 and sent to remote central monitoring unit 30, as
`
`shown in Fig. 1, where it is stored in a database for subsequent processing and presentation to the
`
`user, preferably through a local or global el