A load detector for detecting a load of a subject on a bed (BD) having a caster (CT) includes: a plate portion (1) which is one-fold and which is to be supported above an installation surface (F), on which the load detector is installed, separately from the installation surface; and a slope portion (SL1, SL2, SL3, SL4) which is provided around the plate portion and which is inclined relative to a surface of the plate portion so as to extend between the surface of the plate portion and the installation surface. The plate portion includes: a peripheral part (13); a placing part (11) on which the caster is to be placed, and which is provided inside relative to the peripheral part separately from the peripheral part; and a linking part (12) which links the placing part and the peripheral part. The load detector further includes a strain sensor (G) attached to the linking part, and the slope portion includes at least two pairs of slopes (SL1, SL2, SL3, SL4) each including a pair of slopes opposed to each other such that the placing part is interposed between the pair of slopes.

A ballistocardiogram (BCG), a measurement of cardiogenic whole body movements, is a technique that enables non-invasive cardiovascular monitoring. A main challenge of the BCG signal is that its morphology and amplitude are sensitive to the posture and/or position of the subject during the recording period. The effects of posture on the BCG measured from a subject standing on a weighing scale have been investigated in the literature, but the effects of body posture and/or position on BCG signals measured from a subject lying in a bed have not been quantified. A contemplated method for bed-based BCG recordings includes (1) creating templates for standing BCG signals obtained from subjects in a prior study, and (2) quantifying the distance between these templates and BCG waveforms obtained in different body positions on the bed for a new set of subjects. In addition, an array processing technique is presented, which includes the application of Gaussian weights on a joint probability density function (PDF) and the similarity score called the q-value to assess those PDFs. The Gaussian curve weights the joint probability according to the reference value obtained from the previous inter-beat-interval (IBI) estimations. The PDFs are selected and combined according to their reliability measured by q-values. This array processing significantly reduces the FIR estimation error by comparing the performance of selective channel combinations to the existing multi-channel algorithm.

A person support apparatus includes sensors for monitoring aspects of a person positioned thereon. The outputs from the sensors are used to distinguish between new and prior occupants of the support apparatus, automatically zero an integrated scale system, distinguish between objects and humans on the support apparatus, determine if a person is sleeping or awake, monitor and characterize movement levels of the person, record a log of likely events regarding a support surface of the apparatus, propose identifications of objects added to or removed from the support surface, record force outputs, and/or other purposes. A person's sleep state may also be obtained and forwarded to a remote location. The sleep state data may be used to mute and/or control alerts or indicators, and/or to predict when a person is going to wake up and likely exit the support apparatus.

The present invention relates to a smart diaper changing pad for weighing an infant or toddler and communicating the recorded information wirelessly to a mobile computer. The diaper changing pad incorporates force or mass sensors for measuring weight. The changing and cleaning pad and a separate computing system are wirelessly connected, either directly or through a network capable of both internal and external communication. An application installed on the mobile computer can track measurements from the diaper changing pad and keep a historical record, which may provide peace of mind and insight into a baby's health and development. The key components of the product are a soft pad, a rigid platform, one or more sensors capable of measuring force or weight, a power source, a memory, a processor, and a wireless communication method. The invention can optionally include a display and a number of user inputs such as buttons or switches.

Attributes of a human or animal body are detected by the generation and detection of an electric field. A laminated membrane, connected to a control circuit, is placed over an electrically conductive ground-plane. An upper-mattress is placed above this for supporting a human or animal body. To improve the response of the detector, a response-enhancement-layer of a substantially electrically non-conducting compressible-material containing electrically-conductive-particles, such as carbon particles, is located between the laminated-membrane and the upper-mattress.

A person support apparatus, such as a bed, stretcher, recliner, cot, or the like, includes a frame, a plurality of load cells, a support surface supported by the load cells, a detection circuit, and a controller. The controller determines if any of the load cells are in an error state based upon information from the detection circuit. If the load cells include memory having calibration data stored therein, the controller communicates with the memory and uses the calibration data to determine an amount of weight supported on the surface. The detection circuit may include one or more Wheatstone bridges wherein the controller monitors voltages between midpoints of the Wheatstone bridges. The load cells may include an activation lead that is monitored by the detection circuit and a sensor lead that is used by the controller to determine an amount of weight supported on the patient support apparatus.

A method of pillow customization includes analyzing shapes associated with people through the use of sensors to create analytical data; receiving photos from a subject user through a first computing device and a server; determining a firmness of a mattress of the subject user based on the photos; determining body measurements of the subject based on the photos through one or more algorithms and a second computing device; providing the subject user with a pillow diagram, the pillow diagram having one or more zones, each of the one or more zones being customizable in firmness; receiving one or more subject user inputted selections through the first computing device; and designing a pillow based on the firmness of the mattress, the body measurements, and the one or more subject user inputted characteristics, the pillow being customized to the subject user.

A weight management device is used in a biological information monitoring system configured to monitor biological information of a subject on a bed (BD), based on a detection value of a load detector (LS1, LS2, LS3, LS4) configured to detect a load of the subject. The weight management device includes a housing, a display provided at an outer surface of the housing and configured to display a weight of the subject, based on the detection value, and an attachment portion provided at an outer surface of the housing and attachable to and detachable from the bed.

A changing table, which is placed on a ground or a table and capable of weighting a child, includes a frame, a weighting module and a fabric component. The frame includes a lower frame including a supporting portion for supporting the changing table on a surface of the ground or the table, and an upper frame movably installed on the lower frame. The weighting module includes four load sensors disposed on four corners of the frame and between the lower frame and the upper frame. The fabric component covers the upper frame to form a supporting area for supporting the child. The changing table can measure a first weight of the child before feeding the child and further measure a second weight of the child after feeding the child, so as to determine a difference of the second weight and the first weight of the child as the feeding intake.

An automated system and methods are provided for calibrating an accelerometer of a patient support apparatus using a load cell. The patient support apparatus includes a litter frame and a deck supported by the litter frame, movable between various angled positions. A patient support surface is arranged on the deck and configured to support a patient thereon. The patient support surface has at least one region configured to be disposed at an angular position. A load cell is provided, configured to generate load data including first and second load outputs detected at first and second trend angles with respect to a horizontal plane. An accelerometer is provided, configured to generate angle data including first and second angle outputs representative of the trend angles. A controller in communication with the load cell and the accelerometer determines an error in the angle data and calibrates the accelerometer.