JP2021525146A - Systems and methods for setting the air flow rate in the air mask - Google Patents

Abstract

The present invention provides a system for setting the flow rate of air entering and / or exiting an air mask to configure the atmospheric conditions of the air in the air mask. The system has sensing means and airflow controlling means. The controller receives readings from the detection means and, based on these, controls the air flow level to move the level of detected atmospheric parameters towards a preset target level. The controller uses feedback from the detector to guide each step and performs an iterative adjustment procedure that adjusts the level of air flow in multiple steps.

Description

The present invention relates to a system for setting the air flow rate in an air mask, and a method thereof.

Air masks (or breathing masks) are used in various industries to filter or purify the air inhaled by the user.

For example, air pollution is a global concern. The World Health Organization (WHO) estimates that 4 million people die each year from air pollution. Part of this problem is the air quality of the city's outside air. About 300 cities affected by smog fail to meet national air quality standards.

Official outside air quality standards specify the particulate matter concentration as the mass concentration per unit volume (eg μg / m ^3). Of particular concern are particles with a diameter of less than 2.5 μm (called “PM2.5”) that can penetrate the gas exchange region of the lungs (alveoli), and very small particles (<100 nm). ) Can pass through the lungs and affect other organs, so it is a particle contamination.

The general remedy for this problem is to wear masks that provide clean air by filtration, as this problem does not improve much in the short term, and the mask market in China and elsewhere has been large in recent years. It is showing excitement. For example, it is estimated that there will be 4.2 billion masks in China by 2019.

However, during use, the temperature and relative humidity inside the mask will increase. Coupled with the pressure difference inside the mask relative to the outside, this can make breathing uncomfortable.

A fan that draws air through the filter can be added to the mask to improve comfort and effectiveness. For efficiency and longevity reasons, these are usually electrically rectified brushless DC fans. A fan assisted mask can include an intake fan, an exhalation fan, or both. The intake fan assists in drawing air through the filter and allows a positive mask pressure to be obtained to prevent contaminants from leaking into the mask volume. The exhalation fan assists in ventilation of the mask to ensure complete exhalation of exhaled carbon dioxide.

The advantage of the wearer using the electric mask is that it relieves the slight burden on the lungs caused by inhalation against the resistance of the filter in conventional non-electric masks.

Furthermore, in conventional non-electric masks, inhalation also creates a slight negative pressure in the mask, leading to the leakage of contaminants into the mask, which can be dangerous if the contaminants are toxic. I understand. The electric mask delivers a constant air flow to the face, for example applying a slight positive pressure as described above, as determined by the resistance of the exhalation valve, ensuring that any leak is outward rather than inward. Can be.

Thus, fanned masks improve wearing comfort by reducing temperature, humidity and respiratory resistance, the latter being achieved by controlling the air pressure inside the mask. These parameters can be called "atmospheric parameters".

However, different users typically have different comfort preferences with respect to these atmospheric parameters, for example, one user prefers hotter than another, and one user prefers less humid air than another. You can like it.

In the prior art, it has been proposed to provide a heater or an air conditioner to control the atmospheric condition inside the mask. However, they are bulky, complex and costly.

The inventor has found that it is possible to actually actively adjust the level of atmospheric parameters by controlling the level of air flow supplied by the fan. Therefore, the fanned mask allows the air condition inside the mask to be customized to provide maximum comfort to the user.

However, the problem with this concept is that in practice it is difficult to ensure that the user's preferred level of comfort is achieved. This is because the air flow rate required to achieve a particular value of atmospheric parameters varies depending on the external air condition and the starting condition inside the mask. When using a feedback sensor, it is possible to eventually reach favorable atmospheric conditions, but typically only after a significant time delay, during which the user has already reached. I'm starting to experience a lot of discomfort.

An object of the present invention is to provide an improved means for improving the wearing comfort of a user's air mask.

The present invention is defined by the claims.

According to one aspect of the invention, there is provided a system for setting the flow rate of air entering and / or exiting the air mask, the system.
Sensing means for sensing at least one atmospheric parameter of the air inside the mask,
It has an air flow rate controlling means for controlling the air flow rate entering and / or exiting the air mask, and a controller operably coupled to the air flow rate controlling means and the sensing means, wherein the controller is said to be said. The air flow level is iteratively adjusted based on the measurements so as to obtain one or more measurements from the sensing means and adjust the value of the at least one atmospheric parameter towards a predetermined target value. It is adapted to be.

The adjustment comprises one or more (usually multiple) repetitive adjustment steps, the controller measuring the sensor readings from the sensing means before and / or after each repetitive adjustment of the air flow level. Is adapted to get.

The iterative adjustment step can include one or more (usually multiple) discrete changes in air flow level, and the amount of each discrete change is at least partially relative to the current air flow level. Determined based on.

The present invention is based on the use of an active feedback loop to iteratively adjust the level of air flow to set the level of at least one atmospheric state of air inside the mask. The corresponding at least one atmospheric parameter can include, for example, one or more of air pressure, air temperature, air humidity and carbon dioxide level.

In contrast to prior art techniques, the air flow control device itself is used to control the air condition, avoiding the addition of bulks and the complexity of additional air conditioning condition elements.

Furthermore, by adopting a repetitive adjustment method, rapid adjustment of atmospheric conditions is realized. For example, rather than relying on a pre-prepared look-up table or correlation equation to instantly jump to an estimated air flow level for a desired atmospheric condition, the present invention presents a sensor-based step-by-step approach. adopt. This potentially avoids the waste of energy of driving the air flow control unit to a level that is too high first and then forcibly reducing it. In most cases, it also guarantees a constant convergence towards the desired parameter level, which can also accelerate the realization of the desired atmospheric condition, the result of which is not guaranteed otherwise and is inconsistent and unreliable. May have consequences.

"Repetitive" in the context of the present invention means adjusting the level in multiple steps. The plurality of steps may be separated by, for example, a time delay.

At least one atmospheric parameter of the air inside the mask is set. "Inside" means the inside of an internal area between the user's face or mouth and the mask, separated by the mask.

At least one atmospheric parameter can include one or more of air pressure, air temperature, air humidity, and carbon dioxide levels. Atmospheric parameters may be a combination of individual parameters and may be defined as, for example, points in a multi-parameter space, eg, vectors in a multi-parameter space.

In the example, the air flow rate control means can be an air flow generator such as a fan or a fluid pump such as a blower. However, it may be a different type of air flow control means, and any element suitable for adjusting the air flow entering and / or exiting the mask may be used.

The air flow rate control means may include an air flow generator. Further, a circuit or processor for driving such an air flow generator can be provided.

The sensing means may include one or more individual sensors. Each of the one or more individual sensors may be adapted to sense different atmospheric parameters.

The controller may be adapted to continue iterative adjustment until the value of at least one atmospheric parameter falls within the defined tolerances of the target value.

The tolerance may be determined in advance. It may be fixed, for example, in the program of the controller. It may be in the absolute range. Alternatively, it may be defined by a percentage of target parameter values, such as +/- 5% or +/- 10%.

The controller acquires one or more measurements from the detection means. "Measured value" simply means a reading or sensor output. The output or measurement of the sensing means may give a direct measurement of the atmospheric parameter, or may give a (indirect) indication of the atmospheric parameter, for example via a related parameter.

The controller may be adapted to obtain sensor measurements before and / or after each iterative adjustment of air flow levels.

According to one or more examples, upon reaching the target value of at least one atmospheric parameter, the controller may be adapted to store the level of air flow locally or remotely, and the controller may at least. According to one control mode, it is adapted to set an initial air flow level equal to the previously stored air flow level prior to any adjustment.

According to one or more examples, the controller is communicable with a reference dataset that includes an air flow setting, and when at least one atmospheric parameter target value is reached, the controller has an air flow in the dataset. Adapted to store levels, the controller is adapted to set an initial air flow level equal to the air flow level in the dataset prior to any adjustment according to at least one control mode.

The reference data set may be stored in a memory configured by the system, for example. The reference data set may be stored on a remote server with which the controller can communicate.

According to an advantageous embodiment, the air flow control means can have a maximum air flow level and a minimum air flow level, and the controller is between the minimum air flow level and the maximum air flow level prior to any adjustment. Adapted to set the initial air flow level that is part of. This provides an efficient method for achieving rapid convergence of atmospheric parameters at target values.

The initial air flow level may be set, for example, between the minimum air flow level and the maximum air flow level. In the absence of further information, this usually represents the most efficient starting point for iterative adjustment of air flow levels.

Advantageously, according to any embodiment, the iterative adjustment may include one or more distinct changes in air flow level, each of which is a uniform amount. This technique involves varying the air flow level by one or more steps of a set amount or distance. This is a simple operation method because it is not necessary to determine the magnitude of each adjustment.

According to this series of examples, the adjustment procedure is from the minimum air flow level (to minimize power consumption) to the level that achieves the value of the atmospheric parameter within the defined range of the target atmospheric parameter value. It may include linear iterative adjustments.

According to a series of alternative examples, the iterative adjustment involves one or more discrete changes in the air flow level, and the amount of each discrete change is at least partially relative to the current air flow level. Determined based on.

The "present" can mean a measured or read value of a parameter most recently obtained from the sensing means. Therefore, this can be based on measurements already obtained. Alternatively, the controller may obtain a dedicated measurement before determining the size or amount of adjustment step. This may be done before every step, or just before a subset of one or more steps (to save resources), for example only the first step, or every other step. You may.

Determining the magnitude of each discrete adjustment based on the current air flow level can vary the size of the step depending on how high the air flow level has already reached. Because it can, it provides intelligent and efficient adjustment. For example, if the air flow level is already high now, it may be advantageous to make further changes in relatively small steps.

For example, in a particular set of examples, the amount of each discrete change is a positive amount equal to the set portion of the difference between the current air flow level and the maximum air flow level of the air flow control means. Or a negative amount equal to the set portion of the difference between the current air flow level and the minimum air flow level of the air flow control means.

The set portion may be halved, according to a particular example. Alternatively, any other proportion may be used.

In particular, the controller may be adapted to determine if the current value of at least one atmospheric parameter is above or below the target. At higher levels (eg, if the parameter is temperature or humidity), the controller determines the amount of the next discrete adjustment of the air flow level as the difference between the current air flow level and the maximum air flow level. Set it to half. If the current value is lower than the target value, the next individual adjustment may be set to an amount equal to half the difference between the current level and the minimum air flow level.

An alternative advantageous embodiment is that the iterative adjustment involves one or more discrete changes in air flow level, the amount of each discrete change being at least one target value for atmospheric parameters and at least. It is determined at least in part based on the difference between the current value of one parameter. In this case, the air flow rate is effectively adjusted based on the distance from the current air parameter state to the target state.

The magnitude of each repetitive adjustment may be determined or set proportionally or correlated with the determined difference between the current atmospheric condition and the target atmospheric condition, or is normalized thereof. It may be normalized according to the version, for example, the target value itself.

For example, in one set of examples, the amount of each discrete change is
φ * Δp
Where Δp is the set part of the difference between the current air flow level and the maximum or minimum air flow level of the air flow control means, and φ is the target value of at least one atmospheric parameter. Is equal to the weighting based on the difference between and the current value of at least one parameter.

Whether the maximum or minimum air flow level is used can be selected depending on whether the current atmospheric parameter level is above or below the target level.

Weighting may be given, for example, by a normalized version of the difference between the target value of at least one atmospheric parameter and, for example, the current value of at least one parameter normalized according to the target atmospheric parameter value. In this case, φ is (target value of atmospheric parameter-current value of atmospheric parameter) / target value of atmospheric parameter.

Again, the current value can mean the most recently acquired parameter measurement.

The set (ie, default) part may be half in the example. The amount of this portion may be set manually or automatically. It may be defined in the controller program, for example. It may be adjustable, for example, based on user input or, for example, sensor feedback.

According to any embodiment, the controller may be adapted to set an initial air flow level prior to any adjustment, which level is determined based on the detected user activity level.

The activity level may be a qualitative or quantitative parameter. Activity levels relate to exercise or activities related to movement. Activity levels may be categorized and / or measured into separate activity level types, such as sitting, standing, walking and running. Alternatively, it may be measured and evaluated quantitatively.

The system has activity detection means arranged to detect the user's activity level during use. It has, for example, motion sensors such as heart rate monitors, PPG sensors, pulse sensors and / or accelerometers.

As a specific example, the controller may be adapted to detect any changes in the user's activity level and to change the initial level of air flow in response to the detected changes.

According to one or more embodiments, the control may be adapted to be able to communicate with a local or remote data store that stores the user's personal information and / or preferences. Is adapted to set the initial airflow level based on the user's personal information and / or preferences prior to any adjustment.

According to a set of examples of the present invention, it is possible to provide an air mask having a system according to any of the examples described above or below, the system enters and / or air masks in use. Arranged to set the flow rate of air coming out of.

The air mask may be configured to filter or purify the air inhaled by the user.

The mask is intended to limit the inflow of air, for example, to force the inflowing air through a filter medium provided at an intake / exhaust port for filtering the air prior to supply to the inside of the mask. Can have an intake / exhaust port located in.

An example according to another aspect of the invention provides a method for setting the flow rate of air entering and / or exiting the air mask, which method.
Based on the measurements to obtain one or more measurements of at least one atmospheric parameter of the air inside the mask, and to adjust the value of the at least one atmospheric parameter towards a predetermined target value. It has a step of iteratively adjusting the air flow level entering and / or exiting the mask.

The adjustment can include a plurality of iterative adjustment steps. Measurements of at least one atmospheric parameter are taken before and / or after each iterative adjustment of the air flow level.

Iterative adjustments can include one or more discrete changes in air flow levels, the amount of each discrete change being determined at least in part based on the current air flow level. Discrete changes form iterative adjustment steps.

Examples of the present invention will be described in detail with reference to the accompanying drawings.
FIG. 1 schematically illustrates a first exemplary system according to an embodiment. FIG. 2 schematically shows an example of an air mask incorporating a system according to an embodiment. FIG. 3 schematically illustrates an exemplary air flow rate adjusting procedure performed by a system according to an embodiment. FIG. 4 schematically illustrates parameter optimization in a parameter space using a system according to an embodiment.

The present invention will be described with reference to the drawings. Detailed descriptions and specific examples provide exemplary examples of devices, systems, and methods, but these are for illustration purposes only and are intended to limit the scope of the invention. Please understand that it is not what you did. These and other features, aspects and advantages of the devices, systems and methods of the present invention will be better understood from the following description, the appended claims and the accompanying drawings. It should be understood that the drawings are merely schematic and are not drawn to a certain scale. It should also be understood that the same reference numbers are used throughout the drawing to indicate the same or similar parts.

The present invention provides a system for setting the flow rate of air entering and / or exiting an air mask to construct the atmospheric state of the air in the air mask. The system includes sensing means and air flow control means. The controller receives readings from the detection means and, based on these values, controls the air flow level to move the level of the detected atmospheric parameters towards a preset target level. The controller performs an iterative adjustment procedure that adjusts the level of air flow in multiple steps to guide each step using feedback from the sensing means.

The embodiments of the present invention therefore move the air condition within the mask into a preferred "comfort zone", i.e., a set of one or more atmospheric parameters of air inside the mask, a particular defined range or span, or. It is possible to configure the air condition in the mask to adjust the air flow rate until it is within the permissible range of the specified target value. If there are multiple parameters, this can be understood as moving the atmospheric state within a particular region in the atmospheric parameter space. This area is referred to herein as the "comfort zone."

Atmospheric parameters can include, for example, one or more of temperature, humidity, air pressure and carbon dioxide levels.

The embodiments of the present invention are therefore based on stepwise control of the supply of air flow to the mask to move to a comfortable zone (with proper temperature, humidity and air pressure). A solution is proposed that quickly optimizes air flow to reach a predetermined target air condition.

FIG. 1 schematically illustrates the components of an exemplary system according to one or more embodiments of the present invention. FIG. 2 shows the components of a system incorporated in place within an exemplary air mask 32.

The system 10 includes a fan 16 type air flow rate control means for controlling the air flow rate entering the air mask 32. The fan can also control the air flow rate out of the mask, or an additional fan can be provided to control the air flow rate out of the mask. Fans can be configured between different air flow levels. Different air flow levels correspond to different power levels of the fan (eg, different velocities of the fan) and / or to different velocities of air supplied into and / or from the mask by the fan. Different air flow levels may correspond to different velocities or velocities of air being supplied into and / or from the mask.

The system further comprises a sensor 14 adapted to sense at least one atmospheric parameter, such as temperature, humidity, air pressure and / or carbon dioxide level, when in use. In another example, multiple sensors are provided, each sensor adapted to sense different atmospheric parameters during use.

The sensor 14 and the fan 16 are operably coupled to the controller 20. The controller is adapted to control the fan to constitute the level of perceived atmospheric parameters of air in the air mask 32. In particular, the controller, in use, takes one or more measurements from the sensing means and adjusts the value of at least one atmospheric parameter towards a predetermined target value based on these measurements. Adapted to iteratively adjust the flow level.

When the sensor 14 is adapted to sense a plurality of atmospheric parameters, the controller 20 adjusts the values of the plurality of atmospheric parameters towards a set of predetermined target values or a predetermined target area in the parameter space. As such, it is adapted to iteratively adjust the level of air flow based on the measurements.

As schematically shown in FIG. 2, the sensor 14 is arranged to sense one or more atmospheric parameters of air within the interior 36 of the mask 32, the interior of which is the inner surface of the mask and the user's face and the user's face. / Or means the space or cavity defined between the mouth. The fan 16 is located near the user's mouth to supply the air flow to the mouth area. The fan is mounted in an intake structure 34 arranged so as to extend through the boundary outer wall of the mask 32. This outer wall may function as a filter, for example, and thus may be an in-line filter in series with a fan.

The mask 32 further has an intake / exhaust port, usually including a check valve, which allows the exhaled air to flow out, for example, forcing the inhaled air into the intake / exhaust port. The inflow of air in the intake air is restricted so as to pass through the filter medium provided at the exhaust port. The filter medium can include, for example, a filter material for filtering particulate matter, volatile organic compounds (VOCs) and / or any other contaminants such as gaseous contaminants. Optionally, the filter material can include a carbon medium to block particulate matter, VOCs or other contaminants.

Upon use, the controller 20 is adapted to obtain readings or measurements of one or more atmospheric parameters from the sensor 14, i.e. perform data sampling from the sensor. The sensor may be adapted to provide a reading or sensor output that is a direct representation of the atmospheric parameters in question. Alternatively, the output of the sensor may only indirectly indicate atmospheric parameters. In the latter case, the controller may be adapted to perform processing of the sensor output in order to convert the sensor output into an output that is a direct representation of the parameter in question.

The controller 20 is adapted to iteratively adjust the air flow level based on the acquired sensor readings. In practice, this involves adjusting the voltage source or level of the fan 16. Adjusting the voltage upwards increases the air flow rate, and adjusting it downwards decreases the air flow rate.

Increasing air flow is expected to reduce temperature, humidity and carbon dioxide levels, as well as increase air pressure. Decreasing air flow is expected to increase temperature, humidity and carbon dioxide levels, as well as reduce air pressure.

Preferably, the system 10 further has a wireless communication module for wireless communication with a remote computer, processor or terminal, such as a mobile device such as a smartphone or tablet. This allows wireless control of the system or adjustment of specific settings of the system and / or outputs sensor readings or current state of the system.

In the above example, the fan 16 is provided, but in other examples, another air flow control means may be used instead. In particular, all features and options described herein in relation to the fan may be applied to any other air flow control means that may be used instead.

As mentioned above, the controller 20 is adapted to perform an adjustment procedure, in which the air flow level of the fan 16 adjusts the value of at least one atmospheric parameter towards a predetermined target value. Is iteratively adjusted based on the measured values obtained from the sensing means 14.

There are many different methods for performing this iterative adjustment. These different techniques are outlined in more detail.

According to the simplest first method, the controller 20 starts the fan (air flow device) 16 at the initial air flow level, which is the minimum air flow level of the air flow control device. This is called AF_min. The controller is then adapted to increase the air flow level in a series of one or more steps of equal magnitude until a predetermined target value for at least one atmospheric parameter is reached. This is illustrated in FIG. 3, which schematically shows the increase in air flow level, AF (y-axis, in any unit) as a function of time (x-axis, in any unit). As shown, AF increases linearly in steps of equal magnitude. Arrow 42 indicates the air flow level (AF_i) that has reached the target value of the atmospheric parameters in question (eg, temperature, humidity, blood pressure, carbon dioxide concentration). As shown, the tuning algorithm may simply continue to increase the air flow rate until the parameter is within a certain tolerance of the target value (approximately indicated by Δ).

In a favorable embodiment, the air flow level is increased until the target values for multiple atmospheric parameters are reached. This can be understood by considering a set of two or more atmospheric parameters forming a parameter space, where the controller reaches a particular point in the parameter space, or more preferably a particular region. It is adapted to adjust the air flow level until This point or region is referred to as the "comfort zone" CZ.

This concept is schematically illustrated in FIG. 4, which schematically illustrates a two-dimensional parameter space 44 composed of humidity (drawn on the y-axis) and temperature (drawn on the x-axis). A start point 46 and an end point 48 in the parameter space are shown, each corresponding to different temperature and humidity values. The arrows schematically represent the movement in the parameter space as the air flow level is adjusted by the controller 20. As an example, humidity and temperature are shown to be decreasing. A number of zones 52 within the parameter space are also shown. The adjustment procedure involves iteratively adjusting the air flow rate until the measured atmospheric parameters (temperature and humidity in this case) reach the desired zone within said parameter space. The particular shape, size and distribution of the zones shown in FIG. 4 are merely examples and may differ in other examples.

An exemplary algorithm for the simplest tuning procedure described above is shown below.

[Algorithm 1]
The initial air flow rate level AF_0 at time T = 0 is set to AF_min (the minimum air flow rate level of the fan 16). The measured value of one or more atmospheric parameters is the target value of the parameter obtained from the detection means 14. If not within the specified tolerance Δ, the air flow rate is increased by a set amount: AF_i + 1 = AF_i + ΔAF
Steps 2 and 3 are repeated until the value of the atmospheric parameter is within the specified tolerance of the target value.

Thus, in this example, for each particular air flow level (AF_i), the system determines the values of associated atmospheric parameters (eg, temperature (T) and relative humidity (RH) in mask 32). And determine if the target internal comfort zone has been reached (see description above).

In a more complex example, the distance between the current point or region in the parameter space 14 (ie, the current comfort zone CZ_i) and the target point or region (target comfort zone CZ_target) is determined, as described below. , This is used to guide the subsequent adjustment of the air flow level AF.

Additional steps can be introduced to take into account the possibility that the atmospheric parameters are at too high a level so that the air flow level needs to be reduced, and the controller targets the current value of the atmospheric parameters. Determine if it is higher or lower than the value.

If the value is high (a condition referred to as exceeding the comfort zone threshold), the controller may be adapted to linearly reduce the air flow level, i.e., at time T_i + 1, AF_i + 1 = AF_i_X * ΔAF, where In, X is any integer and may be modified, for example, for different control modes or different system applications.

If the value is lower than the target value, the controller performs a linear increase in the air flow level described above, i.e., at time T_i + 1, AF_i + 1 = AF_i + X * ΔAF, where X is any integer. Yes, for example, may be modified for different control modes or different system applications.

In an alternative embodiment, instead of increasing the air flow level linearly or decreasing the air flow level linearly, the target is the value of one or more atmospheric parameters until the target comfort zone is reached. It may be increased or decreased exponentially until it is perceived to be within the specified tolerance of the value.

The simple linear method described above can be relatively slow for several reasons. In particular, starting air flow adjustment from AF_min in any case adds a significant delay in reaching the target comfort zone, especially if a relatively high air flow level is ultimately required. There is. In addition, increasing the airflow level by the same relatively small amount each time results in a relatively slow adjustment time.

The second method aims to reduce the time required to reach the target value of one or more atmospheric parameters of the air inside the mask. A second exemplary adjustment procedure performed by the controller according to one or more embodiments of the present invention is therefore shown below.

As described above, it is assumed that the air flow control means 16 (fan) is adjustable between the minimum air flow level (AF_min) and the maximum air flow level (AF_max). CZ (AF) is used to indicate a particular point or region in the atmospheric parameter space (a particular "comfort zone") that corresponds to a particular air flow level AF. A particular point or region within the parameter space corresponds to a particular set or range of atmospheric parameter values for temperature and relative humidity, such as (T, RH). CZ_TARGET is used to indicate a set of target values for one or more atmospheric parameters (ie, a target comfort zone).

The distance between two points in the parameter space corresponding to the air flow levels AF1 and AF2 is indicated by CZ (AF1) -CZ (AF2). This "distance" can be understood, for example, as a vector, or simply as a set of ordered differences. A positive distance value indicates that the target comfort zone (a set of targets for one or more parameter values) has not been reached (for example, the parameter value is too low), and a negative distance value indicates that the parameter value targets the target. Indicates that you are overshooting (for example, the parameter value is too high). A distance value of 0 indicates that the comfort zone has been reached accurately. In practice, the distance value indicated by Δ is used to indicate that the achieved value of one or more atmospheric parameters is within the defined acceptable tolerance Δ of the target value.

The second method is based on setting an initial level of air flow between the minimum air flow level (AF_min) and the maximum air flow level (AF_max). This shortens the time required to converge to the target parameter value (target comfort zone) and improves the user experience.

In one example, the initial level of air flow is set between AF_min and AF_max. An exemplary algorithm corresponding to this technique is shown below.

[Algorithm 2]
i = 0
AF_i = (AF_max-AF_min) / 2
If | CZ_TARGET-CZ (AF_i) | <= Δ → Done
ELSE IF [CZ_TARGET-CZ (AF_i)]> 0 THEN
AF_i + 1 = AF_i + X * ΔAF
ELSE IF [CZ_TARGET-CZ (AF_i)] <0 THEN
AF_i + 1 = AF_i-X * ΔAF
i = i + 1
GOTO3

Where ΔAF is a set discrete increase in air flow level and X is any integer, which is set according to, for example, a particular control mode or particular system application. In some examples, X can simply be set to 1.

Alternatively, AF may be adjusted in quantities configured such that the increase is exponential.

According to a more complex example, the amount of adjustment added to or reduced to the air flow level AF each time may vary depending on the current level of air flow. An example of the algorithm based on this method is shown below.

[Algorithm 3]
i = 0
AF_i = (AF_max-AF_min) / 2
If | CZ_TARGET-CZ (AF_i) | <= Δ → Done
ELSE IF [CZ_TARGET-CZ (AF_i)]> 0 THEN
AF_i + 1 = AF_i + [(AF_max-AF_i) / 2]
ELSE IF [CZ_TARGET-CZ (AF_i)] <0 THEN
AF_i + 1 = AF_i- [(AF_i-AF_min) / 2]
i = i + 1
GOTO3

According to the above example, the air flow level will be adjusted in each iterative adjustment (depending on whether the air flow level needs to be increased or decreased in order to approach the target value of one or more atmospheric parameters). ) Increased by an amount equal to half the difference between the current air flow level and the maximum or minimum air flow level. Therefore, this example improves the rate of convergence to the target parameter value by two methods, namely by setting the initial air flow rate level higher than AF_min and by intelligently adjusting each increase in the air flow rate level. ..

It should be noted that this technique assumes a monotonous relationship between air flow and atmospheric parameters (ie, increasing AF means the distance to CZ_TARGET if CZ_TARGET_CZ (AF_i)> 0. Decreasing and reducing AF reduces the distance to CZ_TARGET when CZ_TARGET_CZ (AF_i) <0).

According to a further set of one or more examples, the initial air flow level AF_0 is set according to the previously set air flow level, for example during the previous use of the system, before the system is subsequently switched off. You may. In this set of examples, the controller is adapted to store the level of air flow locally or remotely (eg, in memory) once the target value of at least one atmospheric parameter is reached. The controller is further adapted to set an initial air flow level AF_0 equal to a previously stored air flow level prior to any adjustment in at least one control mode.

Therefore, the system may have local memory to facilitate storage and reading of previous air flow levels. Alternatively, the controller may be able to communicate with a remote data storage device or memory for storing and reading the achieved air flow level.

The controller preferably (if applicable, when operated in the associated control mode) reads the most recently stored air flow level when the switch is turned on and sets the initial air flow level to the previous air flow level. Fitted to set the same as the flow level. Upon reaching the target value of the atmospheric parameter, the controller may overwrite the previously stored air flow level or may store the new current air flow level as a separate entry.

An exemplary algorithm based on this technique is shown below.

[Algorithm 4]
At time T = 0, the controller sets AF_0 to read the previously stored air flow level AF_previous to AF_0 = AF_previous If | CZ_TARGET-CZ (AF_0) | <= Δ → Done
ELSE IF [CZ_TARGET-CZ (AF_0)]> 0 THEN
AF increases, eg, linearly or exponentially, or according to any other scheme, until CZ_TARGET is reached ELSE IF [CZ_TARGET-CZ (AF_0)] <0 THEN
When AF reaches CZ_TARGET, which decreases, eg, linearly or exponentially, or according to any other scheme, until CZ_TARGET is reached, the controller stores the corresponding air flow level AF_new.

As an example, steps 3 to 5 of the above algorithm can be carried out by steps 3 to 6 of [Algorithm 2] or by steps 3 to 6 of [Algorithm 3]. The variants and options described in connection with these algorithms can be applied equally to the above algorithms.

Other exemplary algorithms that follow this approach are shown below.

[Algorithm 5]
At time T = 0, the controller sets AF_0 to read the previously stored air flow level AF_previvous to AF_0 = AF_previvous / 2 If | CZ_TARGET-CZ (AF_0) | <= Δ → Done
ELSE IF [CZ_TARGET-CZ (AF_0)]> 0 THEN
AF increases, eg, linearly or exponentially, or according to any other scheme, until CZ_TARGET is reached ELSE IF [CZ_TARGET-CZ (AF_0)] <0 THEN
When AF reaches CZ_TARGET, which decreases, eg, linearly or exponentially, or according to any other scheme, until CZ_TARGET is reached, the controller stores the corresponding air flow level AF_new.

This example differs only in that the initial air flow level AF_0 is not set to the previously stored value (AF_previous / 2) itself, but to half of this previously stored value. This alternative provides to achieve the target atmospheric parameter values more efficiently when the target atmospheric parameter values are variable between use cases of the system. In some examples, the system may be switchable between different control modes in which Algorithm 4 and Algorithm 5 are used respectively.

According to another set of one or more embodiments, the adjustment procedure performed by the controller is determined based on the detected user activity state, eg, the detected user activity level, prior to any adjustment. It may include setting the initial air flow level AF_0. This active state may include one of a set of alternative options such as sitting, standing, walking, walking speed, eg slow walking, fast walking. Any other activity type, such as cycling, running or boarding, can be included in the optional set.

The activity level may be a qualitative or quantitative parameter. Activity levels relate to exercise or activities related to movement. Activity levels may be categorized and / or measured into separate activity level types, such as sitting, standing, walking and running. Alternatively, activity levels may be quantitatively measured and evaluated.

The system can have activity detection means (activity monitors) arranged to detect the user's activity level during use. This can include, for example, motion sensors such as heart rate monitors, PPG sensors, pulse rate sensors and / or accelerometers. Alternatively, for example, the user can manually enter the activity level of the state.

The controller may be adapted to access a locally or remotely stored look-up table, eg, associating different activity levels or states with different suitable initial air flow levels AF_0.

When the initial air flow level AF_0 is set according to the detected or determined activity level or condition, the controller will continue the iterative adjustment procedure to reach the target value of one or more atmospheric parameters. Is adapted to. This is done, for example, according to Steps 2-6 of Algorithm 2 or Steps 2-6 of Algorithm 3, or according to any other method or example described in the present disclosure or set forth in any claim of the present application. It may be done.

In some examples, contextual information can be combined with activity information. In particular, the controller may be adapted to memorize both the associated air flow level AF and the active state or level in progress once CZ_TARGET is reached. In addition, the controller may be adapted to detect the current air flow level and read the pre-stored air flow level corresponding to the detected activity level when adjusting the air flow level. In this way, the user's previous settings for AF when at a given activity level are used.

In some examples, the controller may be adapted to detect any change in the user's activity level and change the initial level AF_0 of air flow according to the detected change. This change can be detected by an activity monitor. In this case, the controller is adapted to determine the new AF_0. It can be based, for example, on contextual data as discussed in the previous paragraph, or, for example, entries in a database grouped according to the personal characteristics of the user. This option is described in detail below. This allows a quick response when the user changes his or her activity behavior.

According to another set of examples, the distance between the current comfort zone level (current value of one or more atmospheric parameters) and the target comfort zone level (target value of one or more parameters) is the air flow rate. Used in determining the amount of each level adjusted.

Here, the distance means the distance in the parameter space (see the above description with respect to FIG. 4). If only one atmospheric parameter is targeted, the distance is simply the difference between the current and target values of the parameter.

For example, in a particular set of examples, the difference between the current air flow level and either the maximum or minimum air flow level is determined, and then the distance between the determined current and target values of the atmospheric parameters. Weighted according to.
An example of the algorithm based on this method is shown below.

[Algorithm 6]
i = 0
AF_i = (AF_max-AF_min) / 2
If | CZ_TARGET-CZ (AF_i) | <= Δ → Done
ELSE IF [CZ_TARGET-CZ (AF_i)]> 0 THEN
AF_i + 1 = AF_i + [(AF_max-AF_i) * [[CZ_TARGET-CZ (AF_i)] / CZ _NORM ]]
ELSE IF [CZ_TARGET-CZ (AF_i)] <0 THEN
AF_i + 1 = AF_i-[(AF_i-AF_min) * [[CZ_TARGET-CZ (AF_i)] / CZ _NORM ]]
i = i + 1
GOTO3

CZ _NORM is used to normalize the distance from the current comfort zone (current physiological parameter value) to the target comfort zone (target value).

A favorable example is CZ _NORM = CZ (AF_i). Alternatively, CZ _NORM can be set to other suitable values such as AF_min, AF_max.

It should be noted that this technique assumes a linear relationship between air flow and atmospheric parameters (ie, if CZ_TARGET_CZ (AF_i)> 0, increasing AF reduces the distance to CZ_TARGET, and When CZ_TARGET_CZ (AF_i)> 0, reducing AF reduces the distance to CZ_TARGET). However, this technique still works even if the relationships are not strictly linear.

According to one or more examples, the controller may be adapted to switch between the different adjustment methods described above. This may be done dynamically. For example, the controller may first perform the tuning procedure according to Algorithm 1 or Algorithm 2 (eg, for a new mask). For repeated use, the controller can then switch to one or more of the other techniques described in other algorithms. Therefore, a hybrid adjustment method is implemented.

For example, the system may be adapted to implement smart learning capabilities, where different of the adjustment procedures described above are tried, eg, continuously, each targeting atmospheric parameters at the comfort zone level. The velocity brought into CZ_TARGET is recorded. Based on this, the fastest adjustment method (fastest to reach the target) is determined and at least adopted as the default adjustment method for future adjustments. For different users with different comfort zone preferences, certain adjustment techniques prove to reach the target comfort zone level faster than others. This trial procedure allows the most efficient method to be determined and adopted for each given user.

Any combination of the various adjustment procedures described above can be tried, for example all tried one by one or only a subset tried one by one.

By way of example, the trial procedure may also be configured to determine and record the energy efficiency of each adjustment procedure attempted. The procedure is considered energy inefficient if the adjustment procedure results in the air flow level being higher than the required level for the target comfort zone level (ie, passing the required air flow level). This is energy inefficient because energy is wasted by operating the fan at an unnecessarily high level. The procedure is energy efficient if the target comfort zone level is reached without increasing the air flow level above the level required to reach the target comfort zone.

In the example, the adjustment procedure that goes beyond the required air flow level does not have to be considered from other uses, even if the fastest of the remaining adjustment methods is selected as the default for future adjustments. good. Alternatively, the control may be adapted to receive user input indicating a preference between speed and efficiency and evaluate different tuning techniques only for the selected preference metric. Alternatively, a mixture of the two may be used, eg, an efficiency score and a speed score may be derived for each adjustment procedure and the average of the two scores (eg, intermediate) may be taken. The method that achieved the highest average score may then be selected as the default adjustment method for future adjustments.

According to a set of advantageous embodiments, the controller 20 is adapted to communicate with a local or remote data store that stores the user's personal information and / or preferences. In this case, the controller may be adapted to set an initial air flow level based on the user's personal information and / or preference prior to any adjustment.

The system can include a communication module for communicating with a remote terminal, computer or mobile device that houses a remote data store. This may be a wireless communication module. It may have transmitters and receivers that include, for example, one or more antennas for transmission and reception. The communication module can use, for example, ZigBee, RF frequency, Wi-Fi or any other wireless communication protocol to facilitate communication.

A local or remote data store may include, for example, a dataset that stores the optimum air flow level to provide a comfortable air environment in the mask for users with different personal characteristics. These characteristics include, for example, age, height, weight and gender. This database looks up appropriate initial air flow values to initiate the adjustment procedure with the aim of selecting an initial value that is as close as possible to the final value corresponding to the target level selected by the user for one or more atmospheric parameters. May be used for.

An exemplary set of steps that follow this technique is outlined.

First, the controller 20 receives one or more personal characteristics of the user as input. It may be mediated by, for example, an app from a mobile computing device, such as a smartphone, and received wirelessly in the controller. These personal characteristics may be based on the user's pre-stored profile or may be manually entered by the user. As a non-limiting example, personal characteristics entered can include age, weight, height, nationality, and allergic symptoms.

Second, upon receiving the input characteristics, the controller 20 will cluster or classify the users into one of the clusters, groups or categories defined in the database according to the input characteristics. Is adapted to. Clustering or classification may be performed, for example, by K-means clustering or regression analysis.

Third, the initial air flow level AF_0 is derived from the database based on the determined category or cluster in which the user fits. For example, a database can store relationships between initial air flow levels and personal information, such as personal characteristics (which can be represented by curves or straight lines). Alternatively, the database may store a lookup table that associates different groups or clusters of individuals with different specific AF_0 values. Again, the database may store one or more decision trees that allow the derivation of the appropriate air flow level AF_0 based on various personal characteristics.

In addition to or instead, according to the embodiments, the control is adapted to add or update data to the database according to the information obtained by the use of the mask by a given user. For example, the database may use one or more of age, height, weight, nationality, and allergies as inputs to characterize the user. Other properties such as the method by which the air mask is worn, or the duration during which the air mask is worn (eg, the average duration) are also used.

These properties can be used to cluster or classify users and / or to recluster or reclassify database entries. The information obtained about the air flow level used by the clustered or classified users is then used to update the database or add data. In particular, the controller can acquire, eg, store, air flow levels associated with the user's preferred atmospheric parameter settings. These can be used to update the database and, as mentioned above, improve results when using the database to determine initial air flow settings for future users.

The data in the database may be used in other ways to further improve the coordination procedures performed by the controller.

For example, as described above, Algorithm 6 assumes a linear relationship between air flow levels and one or more atmospheric parameters (comfort zones). By collecting data from a population of connected users (as described above), the actual relationships between these parameters can be determined and stored (possibly further hierarchical based on user characteristics). It can also be converted or classified). Thus, the derived relationship curves collected from the user population of connected masks can be used, for example, in constructing adjustment algorithms performed on new unconnected masks and existing masks. Yes (because the relationship between parameters and air flow is better known).

As described above, the embodiment utilizes a controller. The control can be implemented in various ways, using software and / or hardware, to perform the various functions required. A processor is an example of a controller that uses one or more microprocessors that may be programmed using software (eg, microcode) to perform the required function. However, the controller may be implemented with or without a processor, or dedicated hardware for performing some functions and a processor for performing other functions (eg,). It may be implemented in combination with one or more programmed microprocessors and related circuits).

Examples of controller components used in the various embodiments of the present disclosure include, but are not limited to, conventional microprocessors, application specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs).

In various practices, the processor or controller may be associated with one or more storage media such as volatile and non-volatile computer memory such as RAM, PROM, EPROM and EEPROM. The storage medium, when executed on one or more processors and / or controllers, may be encoded by one or more programs that perform the required functions. The various storage media may be fixed within the processor or controller, or may be transported such that one or more programs stored on the storage medium can be read into the processor or controller. You may.

From the drawings, the present disclosure and the examination of the appended claims, those skilled in the art who practice the claimed invention can understand and implement other variations of the disclosed embodiments. In the claims, the word "have" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude more than one. The mere fact that the particular means are described in separate dependent claims does not indicate that the combination of these means cannot be used in an advantageous manner. No reference code in the claims should be construed as limiting the scope.

Claims (14)

In a system for setting the flow rate of air entering and / or exiting an air mask, the air mask is used.
Sensing means for sensing at least one atmospheric parameter of air in the air mask.
The controller comprises an air flow rate controlling means for controlling the air flow rate entering and / or exiting the air mask, and a controller operably coupled to the air flow rate controlling means and the sensing means. ,
One or more measurements are taken from the sensing means, and the level of the air flow rate is iteratively adjusted based on the measurements to adjust the value of at least one atmospheric parameter towards a predetermined target value. Fitted to
The adjustment comprises a plurality of iterative adjustment steps.
The controller is adapted to obtain sensor measurements from the sensing means before and / or after each iterative adjustment of the air flow level.
A system in which the iterative adjustment involves one or more discrete changes in air flow levels, the amount of each such discrete change being determined at least in part based on the current air flow level. The system of claim 1, wherein the controller is adapted to continue the iterative adjustment until the value of the at least one atmospheric parameter is within a defined tolerance of the target value. The controller is communicable with a reference data set that includes a reference air flow rate setting, and upon reaching the target value of the at least one atmospheric parameter, the controller sets the air flow level to the reference data set. Adapted to remember, the controller is adapted according to at least one control mode to set an initial air flow level equal to the air flow level in the reference dataset prior to any adjustment. The system according to claim 1 or 2. The system according to any one of claims 1 to 3, wherein the at least one atmospheric parameter comprises one or more of air pressure, air temperature and air humidity. The air flow control means has a maximum air flow level and a minimum air flow level, and the controller is a part between the minimum air flow level and the maximum air flow level prior to any adjustment. Any of claims 1 to 4, adapted to set an initial air flow level, optionally said that the initial air flow level is between the minimum air flow level and the maximum air flow level. The system described in item 1. The system further comprises an activity detection means for detecting the activity level of the user.
The controller is adapted to set an initial air flow level determined based on the detected activity level of the user prior to any adjustment, and optionally, the controller is the user. The system according to any one of claims 1 to 4, wherein any change in the activity level of the above is detected and adapted to change the initial level of the air flow rate in response to the detected change. The control is adapted to be able to communicate with a local or remote data store that stores the user's personal information and / or preferences, and the control prior to any adjustment. The system according to any one of claims 1 to 6, adapted to set an initial air flow level based on the personal information and / or user preference. The amount of each of the discrete changes is a positive amount equal to the set portion of the difference between the current air flow level and the maximum air flow level of the air flow control means, or the current amount of change. The system according to any one of claims 1 to 7, wherein the amount is a negative amount equal to a set portion of the difference between the air flow level and the minimum air flow level of the air flow control means. The iterative adjustment comprises one or more discrete changes in the air flow level, the amount of each discrete change being the target value of the at least one atmospheric parameter and the at least one parameter. The system according to any one of claims 1 to 8, which is determined at least in part based on the difference from the current value of. The amount of each of the discrete changes is equal to φ * Δp, where Δp is the difference between the current air flow level and either the maximum or minimum air flow level of the air flow control means. The system of claim 9, wherein φ is a weighting based on the difference between the target value of the at least one atmospheric parameter and the current value of the at least one atmospheric parameter. The air mask according to any one of claims 1 to 10, which is arranged to be used for setting the flow rate of air entering and exiting the air mask. The air mask according to claim 11, wherein the air mask is for filtering or purifying the air inhaled by the user. The air mask limits the inflow of air in order to forcibly pass the inflowing air through a filter medium provided in the intake / exhaust port for filtering prior to the supply to the inside of the air mask. The air mask according to claim 11 or 12, which has an intake / exhaust port arranged in. A method for setting the flow rate of air entering and / or exiting the air mask.
The step of acquiring one or more measurements of at least one atmospheric parameter of the air inside the air mask.
There is a step of iteratively adjusting the level of air flow entering and / or exiting the airmask based on the measurements so that the value of at least one atmospheric parameter is adjusted towards a predetermined target value. However, the adjusting step includes a plurality of iterative adjustment steps.
Measurements of at least one atmospheric parameter are obtained before and / or after each repetitive adjustment of the air flow level, the repetitive adjustment being one or more discrete changes in the air flow level. A method in which each of the discrete amounts of change is determined at least in part based on the current air flow level.

Images