Bed with adaptive portions

Abstract

A bed (102) with adaptive portion (108) is disclosed. The bed (102) includes a surface grid (106). The surface grid (106) includes at least one adaptive portion (108), at least one actuator (210) coupled to the at least one adaptive portion (108), a controller (608), and a memory (610) communicably coupled to the controller (608). The memory (610) may include a set of instructions which when executed by the controller (608), causes the controller (608) to determine a flawed posture corresponding to a user (902). The controller (608) generates an actuation signal comprising information associated with a corrected posture corresponding to the flawed posture to at least one actuator (210). Further, controller (608) adapts the at least one actuator (210) based on the actuation signal for adapting the at least one adaptive portion (108) in accordance with the corrected posture for correcting the flawed posture of the user (902).

Description

PATENT APPLICATION

[0001] FOR

[0002] BED WITH ADAPTIVE PORTIONS

[0003] BY

[0004] KALYANA RAGHAVA TEJA VINUKOLLU

Claims

I / We Claim:A method, comprising:receiving, by a controller, sensor data associated with a user, based on the user being in contact with at least one adaptive portion within a surface grid of a bed, wherein the sensor data is generated by at least one sensor in the at least one adaptive portion;determining, by the controller, one or more attributes of the user based on the sensor data;determining, by the controller, a flawed posture corresponding to the user based on the one or more attributes of the user, whereinthe flawed posture corresponds to a deviation of the one or more attributes of the user from a correct posture, andthe correct posture is based on dataset on specific body alignment;generating, by the controller, an actuation signal comprising information associated with the correct posture corresponding to the flawed posture, for at least one actuator, wherein the at least one actuator is coupled to the at least one adaptive portion in contact with the user;controlling, by the controller, the at least one actuator based on the actuation signal; andadjusting, by the controller, the at least one adaptive portion based on the controlling of the actuator and the correct posture, for correcting the flawed posture of the user.The method of claim 1, wherein the controlling of the at least one actuator comprises:actuating, in real time, the actuator to move, based on the correct posture, for adjusting the flawed posture of the user to the correct posture.The method of claim 1, whereinthe sensor data is from a sensor unit,the sensor unit is underneath the at least one adaptive portion in contact with the user, andthe determining of the flawed posture further comprises:processing, by the controller using a machine learning model, the one or more attributes corresponding to the user for the determining of the flawed posture.The method of claim 3, wherein the one or more attributes of the user comprises at least one of:historical and real-time activities of the user,a real-time posture of the user,changes in real-time posture of the user based on ambient conditions,physical characteristics of the user, andbiometric characteristics of the user.The method of claim 1, further comprising:determining, by the controller, using a machine learning model with the one or more attributes of the user:the correct posture corresponding to the flawed posture; anda predicted posture corresponding to the user, wherein the machine learning model is a neural network trained with historical sensor datasets and correct posture datasets.

6. The method of claim 1, wherein each actuator of the at least one actuator comprises:a telescopic arm that is positioned at a base of a main frame, wherein the telescopic arm is coupled to a bottom of the at least one adaptive portion;based on the actuation signal, the actuator is configured to move the telescopic arm to one of raise or lower the at least one adaptive portion corresponding to the flawed posture.The method of claim 1 and further comprising:determining, by the controller, the user falling off from the at least one adaptive portion due to the flawed posture, based on the sensor data; andcontrolling, by the controller, the at least one adaptive portion on a perimeter of the surface grid for preventing the user from falling off from the at least one adaptive portion.

8. A bed, comprising:a surface grid comprising:at least one adaptive portion;at least one actuator coupled to the at least one adaptive portion;a controller; anda memory communicably coupled to the controller, wherein the memory comprises a set of instructions which when executed by the controller, causes the controller to:receive sensor data associated with a user, based on the user being in contact with the at least one adaptive portion within the surface grid of the bed, wherein the sensor data is generated by at least one sensor in the at least one adaptive portion;determine one or more attributes of the user based on the sensor data;determine a flawed posture corresponding to the user, based on the one or more attributes of the user, whereinthe flawed posture corresponds to a deviation of the one or more attributes of the user from a correct posture, andthe correct posture is based on dataset on specific body alignment;generate an actuation signal comprising information associated with the correct posture corresponding to the flawed posture, for the at least one actuator, wherein the at least one actuator is coupled to the at least one adaptive portion in contact with the user;control the at least one actuator based on the actuation signal; andadjust the at least one adaptive portion based on the controlling of the actuator and the correct posture, for correcting the flawed posture of the user.The bed of claim 8, wherein the control of the at least one actuator comprises:actuation, in real time, of the actuator to move, based on the correct posture, to adjust the flawed posture of the user to the correct posture.

10. The bed of claim 8, whereinthe sensor data is from a sensor unit,the sensor unit is underneath the at least one adaptive portion in contact with the user, andthe determination of the flawed posture, the set of instructions causes the controller to:process using a machine learning model, the one or more attributes corresponding to the user for the determination of the flawed posture.The bed of claim 8, wherein the one or more attributes of the user comprises at least one of:historical and real-time activities of the user,a real-time posture of the user,changes in real-time posture of the user based on ambient conditions,physical characteristics of the user, andbiometric characteristics of the user.The bed of claim 8, wherein to determine the corrected posture, the set of instructions further causes the controller to:determine using a machine learning model with the one or more attributes of the user:the correct posture corresponding to the flawed posture; anda predicted sleep patterns corresponding to the user, wherein the machine learning model is a neural network trained with historical sensor datasets and correct posture datasets.The bed of claim 8, wherein each actuator of the at least one actuator comprises:a telescopic arm positioned at a base of a main frame, wherein the telescopic arm is coupled to a bottom of the at least one adaptive portion,based on the actuation signal, the actuator is configured to move the telescopic arm, to one of raise or lower the at least one adaptive portion corresponding to the flawed posture.The bed of claim 13, wherein the telescopic arm is coupled to a lifting column, wherein the lifting column is accommodated between the bottom of the at least one adaptive portion and the telescopic arm.The bed as claimed in claim 8, wherein the set of instructions further causes the controller to:determine the user falling off from the at least one adaptive portion within the surface grid due to the flawed posture, based on the sensor data; andcontrol the at least one adaptive portion on a perimeter of the surface grid to prevent the user from falling off from the at least one adaptive portion.An application server, comprising:a controller; anda memory communicably coupled to the controller, wherein the memory comprises a set of instructions which when executed by the controller, causes the controller to:receive sensor data associated with a user, based on the user being in contact with at least one adaptive portion within a surface grid of a bed, wherein the sensor data is generated by at least one sensor in the at least one adaptive portion;determine one or more attributes of the user based on the sensor data;determine a flawed posture corresponding to the user, based on the one or more attributes of the user whereinthe flawed posture corresponds to a deviation of the one or more attributes of the user from a correct posture, andthe correct posture is based on dataset on specific body alignment ;generate an actuation signal comprising information associated with the correct posture corresponding to the flawed posture, for at least one actuator, wherein the at least one actuator is coupled to the at least one adaptive portion in contact with the user;control the at least one actuator based on the actuation signal; andadjust the at least one adaptive portion based on the controlling of the actuator and the correct posture, for correcting the flawed posture of the user.The application server of claim 16, whereinthe sensor data is from a sensor unit,the sensor unit is underneath the at least one adaptive portion in contact with the user, andfor the determination of the flawed posture, the set of instructions causes the controller to:process, using a machine learning model, the one or more attributes corresponding to the user for the determination of the flawed posture.The application server of claim 16, wherein the one or more attributes of the user comprises at least one of:historical and real-time activities of the user;a real-time posture of the user;changes in real-time posture of the user based on ambient conditions;physical characteristics of the user; andbiometric characteristics of the user.The application server of claim 18, wherein for the determination of the correct posture, the set of instructions further causes the controller to:determine using a machine learning model with the one or more attributes of the user:the correct posture corresponding to the flawed posture; anda predicted posture corresponding to the user, wherein the machine learning model is a neural network trained with historical sensor datasets and correct posture datasets.BED WITH ADAPTIVE PORTIONS

Images