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 an unbiased recommendation.
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 answer a few basic questions (height, age gender, etc.), and then lie on a test bed for a few moments, 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 partner 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.
In the accompanying drawings,
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 (
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 anatomical zones. 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 more lengthy 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 partner is present in the store. That person can answer the short questionnaire, and be measured on the test bed. Then, by completing the long-form questionnaire for a partner, and having that information processed by the second algorithm, a net recommendation can be generated, based on a calculation 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 questionnaire and sensor 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
One initiates the short-form process by striking the Start button (
In
Before the subject lies on the test bed, it must be set up by a program (
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 (
Next, if the subject was the first person during the session to lie on the bed, he is asked (
If the subject answered that his partner was not present, he is offered an opportunity to answer the long-form questionnaire, represented in
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.
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 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 show the user the selected 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.
This applicationThis is a Reissue Application of application Ser. No. 10/849,124 filed May 20, 2004, now U.S. Pat. No. 6,990,425, which is a continuation of application Ser. No. 10/346,117, filed Jan. 17, 2003 now U.S. Pat. No. 6,741,950, which was a continuation of Ser. No. 09/722,592, filed Nov. 28, 2000, now U.S. Pat. No. 6,571,192. The entire disclosures of the prior applications and patents are hereby incorporated by reference in their entirety.
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Number | Date | Country | |
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Parent | 10346117 | Jan 2003 | US |
Child | 10849124 | US | |
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Child | 10346117 | US |
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Parent | 10849124 | May 2004 | US |
Child | 12019343 | US |