Automatic mattress selection system

Abstract

A mattress selection system comprises a test bed including a box spring and a compartmented air mattress which generates electrical outputs indicative of the weight distribution of a subject. The sensor outputs are processed automatically, in conjunction with answers to a questionnaire, to generate a recommendation of which of a selection of available mattress systems, is most suitable for the subject.

Description

BACKGROUND OF THE INVENTION

This invention relates to a system for aiding bedding purchasers in their selection of a mattress and box spring combination according to their physiology and habits.

A good night's sleep is so important that most people are willing to pay a premium for a mattress system which is particularly comfortable. The increased recognition of the health benefits of sleeping well makes such expenditures rational.

Many people find the experience of purchasing bedding confusing and dissatisfying. Reasons for this include: (1) mattress purchases are made only a few times per lifetime, (2) one cannot examine the interior of the product being purchased and must therefore (3) rely on the expertise of commissioned salesmen who may tend to recommend products they have in stock, and (4) it is difficult to comparison price shop because of the very large number of mattress manufacturers and models, and the absence of standardized mattress ratings.

It would be helpful to bedding purchasers to have an automatic system which could analytically and fairly measure physiological parameters important to mattress selection, and then automatically recommend a bedding product most suitable for the purchaser. Such a system, if placed in a store, would give customers a preliminary idea of the factors involved, and the products suited for them, before talking to a salesman.

SUMMARY OF THE INVENTION

An object of the invention is to enable mattress distributors and the like to measure the sleeping attributes of potential customers at sites convenient to the customers, so that properly designed bedding can be selected.

It is important that a measuring system be fast, accurate and not embarrassing or uncomfortable for the subject. Therefore, it is an object of this invention to provide a measuring system which requires only that the subject lie on a test bed for a few moments, and answer a few basic questions (height, age gender, etc.) in order to produce a recommended bedding selection.

Another feature of the invention is to enable a purchaser who does not have access to the test bed to obtain a mattress recommendation based entirely on answers to a questionnaire. For example, a person buying a mattress could obtain a recommendation for him- or herself by the method described above, and then in addition enter information about the absent spouse so that a bedding recommendation for the couple jointly could be obtained. This questionnaire-only method could also be used by people shopping remotely, e.g., over the internet.

These and other objects are attained by mattress selection system as described below.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings,

FIG. 1 is an exploded isometric view of a test bed embodying the invention;

FIGS. 2-14 are schematic representations of a method for processing sleep attribute data and developing a bedding recommendation. In particular, FIG. 2 represents a main menu of a computer display;

FIG. 3 shows a graphic submenu continuing from option 4 of FIG. 2 , and

FIG. 4 shows a further submenus continuing from option 7 of FIG. 3 .

FIG. 5 illustrates the starting sequence of the diagnostic system.

FIG. 6 shows the flow of a questionnaire.

FIG. 7 is a flow diagram illustrating a method of setting up a diagnostic bed.

FIG. 8 shows the septs of obtaining a physiological profile a subject.

FIG. 9 illustrates an image base.

FIGS. 10-14 show, in successive linked diagrams, a method for determining a sleep coefficient based on questionnaire data and physiological data.

DESCRIPTION OF THE PREFERRED EMBODIMENT

A sleep analysis system for aiding bed selection comprises a measuring apparatus 10 which produces electrical outputs that are processed by a computer 12 which processes the outputs in a manner directed by a program ( FIGS. 2-14 ) to generate an output in the form of a bed coefficient which can be used to select bedding.

The test bed comprises a frame 20 which supports a box spring 22 and a compartmented air mattress 24 . The cells of the air mattress are divided into four zones corresponding to (1) the head and shoulders, (2) the lumbar region, (3) the hips and (4) the feet of the subject. When a subject lies on the mattress, different pressures are produced at each zone. The pressure readings are converted to electrical signals by appropriate transducers, not shown, and those signals are communicated over a multi-conductor cable 30 as inputs to a central processing unit, for example a personal computer 40 . The computer reads the various inputs and processes them, in accordance with instructions from a program (software) which has been loaded on the computer previously, or which perhaps is accessed through a network such as the internet.

While it would be possible to custom-build a mattress system precisely for the subject, from the data collected, it is presently contemplated to provide the store with a small number (e.g., four) of mattress systems spanning a range of characteristics, and to provide a recommendation for one of those, based on the closest fit of the data.

We have found that the data from the pressure-sensor array can be substantially enhanced by eliciting additional information from the subject. A brief questionnaire is used for this purpose. There is an inverse relationship between the amount of questionnaire data needed and the amount of sensor data available. We have found that, in addition to the sensor data, only four questions need be answered: the subject's age, height, gender, and chronic pain state. Where sensor data cannot be obtained, a thirty-two question questionnaire is used, the extra questions making up for the absence of measured data.

In the first instance, the questionnaire data is processed in conjunction with the sensor data by a computer program or application (software) which processes the inputs automatically according to a first algorithm contained in the software. Where sensor data is not available, the answers to the longer questionnaire are processed alone, by a second algorithm.

It is useful to have both algorithms available in a store-based system, so that information can be obtained not only from shoppers, but also for absent sleep partners. Suppose, for example, one spouse is present in the store. That spouse can be measured on the test bed, and can answer the short questionnaire. Then, by completing the long-form questionnaire for her partner, and having that information processed by the second algorithm, a net recommendation can be generated, based on an average of the results of both computations.

The second algorithm is useful independently, as well, for example by people shopping via the internet, who lack access to the test bed and cannot produce sensor-based data. We believe the combination of sensor and questionnaire data produces the best results, but we have found the long-form questionnaire data to produce quite reliable results as well.

A particularly preferred implementation of the invention is shown in schematic form in FIGS. 2-14 . As shown in FIG. 2 , the welcome page of the monitor in the kiosk has six options, any of which can be selected by pointing to and clicking on the option (if a mouse is used), or by touching the item, if a touch screen is used. Alternatively, a keyboard could be used to make selections. (From here on, it will be assumed the display has a touch screen, and that selections are made simply by touching a particular area on the screen.)

The main menu options are identified by numerals 1 - 6 . Options 1 , 2 , 3 , 5 and 6 lead to informational screens, or to applications (programs and data) not directly related to the present invention. They are therefore not discussed further. Selection of option # 4 invokes the “Sleep Machine” applications embodying this invention. There are two separate algorithms, as mentioned above; these are represented by options 7 and 8 in FIG. 3 , which represents the two choices presented in the screen displayed upon selection of option 4 . Option 7 is the short-form method mentioned above.

One initiates the short-form process by striking the Start button ( FIG. 4 ) on the display. A virtual keyboard is then displayed, allowing one to “type” by touching the illustration. If the exact phrase “SHUT DOWN NOW” ( FIG. 5 ) is entered, the program is ended. If the exact phrase “SET UP AIR BED” is entered, the air bed pressure is balanced, and hardware buffers are emptied. These exact phrases are expected to be entered only by store personnel. The set up command should be done daily. Any other entry is written to the screen.

In FIG. 6 , the user is then prompted to enter his height. Following validation of the height data (to be within a predetermined range), the entry is saved to a variable. Next, the user is prompted to enter his age, which is similarly validated and saved to a variable. A gender entry is similarly saved to a variable. Lastly, the user is asked whether he has occasional pain in the neck, shoulder, middle back, lower back, or other areas, and selects one or more items from that list, the selections being saved to variables.

Before the subject lies on the test bed, it must be set up by a program ( FIG. 7 ) which inflates the pressure cells, checks for errors in the bed, and resets variables from base weight distributions.

After the bed has been set up, the user is instructed to lie supine (face up) on the bed. An associate strikes a “Start Profile” button on the screen (FIG. 8 ). As the person lies on the bed, the pneumatic pressure in the four zones of the air mattress are monitored. The subject's breathing and body image ( FIG. 9 ) may be represented graphically on the screen during this process. After a brief time, sufficiently long to achieve steady-state readings, the program samples the pressure signals, and combines them with the results of the questionnaire, to generate a “coefficient” representing the bedding (mattress and box spring combination) choice most appropriate for the subject. This coefficient is displayed prominently on the screen, and stored in memory.

Next, if the subject was the first person during the session to lie on the bed, he is asked ( FIG. 8 ) whether he has a sleep partner. If there is an affirmative reply, and the second person is present, the second person is invited to respond to the short form questionnaire, following which he is instructed to lie on the bed, and the process described above is repeated. His values are combined with those of the first person, and a bed coefficient is determined which represents the best compromise choice for the two people.

If the subject answered that his partner was not present, he is offered an opportunity to answer the long-form questionnaire, represented in FIGS. 10-14 , for the second person. Here, the questions are more numerous, but nevertheless should be answerable by an intimate partner: gender, height, weight, clothing sizes, age range and so on. Reasonable default values are used if a question is left blank. The body image on the screen is altered to fit the answers to the questionnaire, as if the person were lying on the test bed.

A subsequent set of questions involve arthritic pain: multiple locations of such pain may be selected, and a graphic pain representation is added to the image. A selection may be toggled between true and false by striking it repeatedly.

The next set of questions related to bed-related pain: whether the missing person goes to bed with, or wakes up with, neck, shoulder or back pain. Answers are stored to variables, and the image representing the person is altered to illustrate the pain as appropriate.

The final set of questions elicit lifestyle information: whether

the person's sleep is disrupted,

he feels awake all day long,

he wakes up more than five times per night,

he takes naps given the opportunity,

he feels he sleeps well,

he smokes,

he drinks caffeinated beverages,

he does so after 2:00 p.m.,

he is active in sports,

he exercises regularly.

The answers to the long-form questionnaire are processed and a best-fit bed coefficient for the missing partner is produced. This is combined with the first person's coefficient to produce a compromise best fit for the two people. Now the sales associate can help the user select a bed having the correct bed coefficient, and the shopper will have greater assurance his selection will be a correct one.

Since the invention is subject to modifications and variations, it is intended that the foregoing description and the accompanying drawings shall be interpreted as only illustrative of the invention defined by the following claims.

Claims

1. A method of recommending a mattress system from a plurality of mattress systems having different physical characteristics, said method comprising steps ofproviding a test bed with sensors for producing signals representative of localized pressures at various points from the weight of a person lying on the test bed, having a person recline on the test bed so as to generate said signals, securing from the person objective answers to questions about his physiological parameters, automatically processing said signals and said answers in conjunction to identify which of said plurality of mattress systems is physiologically most suitable for said person.

2. The invention of claim 1, wherein said questions elicit the person's age, the person's height, the person's gender and locations of the person's chronic pains.

3. A bedding marketing system including a plurality of mattress systems having different physical characteristics,a test bed with sensors for producing signals representative of localized pressures at various points from the weight of a person lying on the test bed, questionnaire means for securing from the person objective answers to questions about his physiological parameters, and means for automatically processing said signals and said answers in conjunction to identify which of said plurality of mattress systems is physiologically most suitable for said person.

4. The system of claim 3, wherein said questions elicit the person's age, the person's height, the person's gender and locations of the person's chronic pains.

5. The system of claim 3, wherein said questions elicit locations of pains the person goes to bed with, and wakes up with.

6. The system of claim 3, wherein said questions elicit lifestyle information including caffeine ingestion, sleeping habits, smoking habits, and exercise habits.