A height-adjustable pillow includes: a cervical pillow including an outer shell and contents filled inside the outer shell, and wall parts formed to protrude from both sides of the loading part; side pillows including side-of-face contact parts, which are attached to both sides of the cervical pillow and have a plurality of elastic pads formed in the same shape and stacked therein, and fine height-adjusting parts comprising a plurality of slim pads stacked at the lower portions of the side-of-face contact parts and cover bodies which are finished by respectively encompassing the outer surfaces of the plurality of slim pads and being thermally fused to the edge portions thereof and which have friction increasing parts provided on the outer surfaces thereof; wing parts for connecting the lower portions of the cervical pillow and the side pillows; and an outer cover in which all constituent parts are accommodated and fitted.

Body support cushions are disclosed. The cushions comprise a plurality of separate and distinct consecutive layers overlying over each other in a depth direction. Each layer includes thermal effusivity enhancing material with a thermal effusivity greater than or equal to 2,500 Ws.sup.0.5/(m.sup.2K), and the total thermal effusivity of increases from layer to layer in the depth direction. The plurality of layers include a plurality of phase change layers that each comprise a solid-to-liquid phase change material (PCM) with a phase change temperature within the range of about 6 to about 45 degrees Celsius. The total mass of the PCM increases from layer to layer in the depth direction. At least one layer of the plurality of phase change layers includes a gradient distribution of the mass of the PCM and the amount of the thermal effusivity enhancing material thereof that increases in the depth direction.

The present disclosure provides for a coated flexible open-cell polyurethane foam structure. The coated flexible open-cell polyurethane foam structure includes a flexible open-cell polyurethane foam having a first major surface and a second major surface opposite the first major surface. The coated flexible open-cell polyurethane foam structure further includes a flexible heat conductive material covering 30 to 90 percent (cov., expressed in %) of a surface area of the first major surface of the flexible open-cell polyurethane foam in a predefined shape to provide one or more gaps exposing the flexible open-cell polyurethane foam between defined edges of the flexible heat conductive material, where each gap of the one or more gaps has a gap width according to Formula I: gap width (mm) ≤−0.196×cov. (%)+20.6 (Formula I) where a total surface area of the one or more gaps provides 70 to 10 percent of the surface area of the first major surface of the flexible open-cell polyurethane foam.

A pillow is provided herein which includes a cover having opposing first and second panels. A gusset perimetrically bounds, and joins, the first and second panels. The gusset is formed of an open cell construction. Compliant fill material is disposed within the cover. Advantageously, with the subject invention, a pillow is provided allowing for lateral ventilation between opposing panels. This permits a cooling effect while a user is resting or sleeping.

A care travel system which provides comfort and relief from headaches. It holds an ice pack or other chilled items against the head, neck, and shoulders. The device counteracts fevers when facing an illness. It effectively eliminates the need to take medication, which can make people sleepy and groggy or cause an allergic reaction. As designed it prevents soreness and discomfort that typically manifests during travel.

A bedding system uses a convolutional neural network (CNN)-based machine vision to makes adjustments for comfort and/or support. The machine vision process identifies a body position by using a trained CNN that receives a pressure image and identifies a body position. The body position may be determined by classifying the pressure image into a predetermined body position classification. The machine vision process includes at least one trained CNN that determines joint locations. The machine vision tracks pressure accumulated at joints over time.

A comfortable inflatable pillow, manufactured to be affordably priced, designed to withstand the weather challenges associated with beaches, and other outdoor settings, by utilizing soft fabric that wicks away water and sheds sand, that has an attached pouch that can be filled with sand, or other weighted objects, to prevent the pillow from being blown around in windy conditions, that contains an internal pocket that can accommodate a tailor-made cooling and heating gel pack for hot or cold external temperatures, and that provides an optional incline position for added comfort when reading or surveying the landscape.

A pillow is provided having an elongated main body having a first end and a second end and a length from the first end to the second end. The pillow may further have a first notch at a top edge of the elongated main body adjacent the first end and a second notch at the top edge of the elongated main body adjacent the second end. The pillow may then have a first pocket at an inner surface of the elongated main body between the first notch and a bottom edge of the elongated main body and a second pocket at the inner surface between the second notch and the bottom edge.

A product and process for reducing discomfort due to heat and moisture evolved during a period of contact between living skin and a cushioning material, using a thermally conductive cushioning device, having a first layer of a moisture management fabric, a second layer of a thermally conductive web, and a third layer of a thermally insulative cushioning material.

A bedding system uses a convolutional neural network (CNN)-based machine vision to makes adjustments for comfort and/or support. The machine vision process identities a body position by using a trained CNN that receives a pressure image and identifies a body position. The body position may be determined by classifying the pressure image into a predetermined body position classification. The machine vision process includes at least one trained CNN that determines joint locations. The machine vision tracks pressure accumulated at joints over time.