“Ergonomic Sitting Arrangement for Human Posture Correction”

Abstract

Sitting in a particular posture for a long duration may cause serious health damage to human body, such as myopia, humpback, cervical spine diseases etc. This research paper classifies the sitting postures of sedentary people involved in daily official jobs and study areas. According to medical research, human biological function and advanced ergonomical technology, the collected data from the sitting postures depict the focal point of this innovative approach to design the smart chair. A solution has been proposed by utilizing the ANOVA (Analysis of Variance) analysis method to create an intelligent decision-making environment. By analyzing the wrong positions of sitting on a chair of 26 persons involved in the process, different sitting postures can be identified. By providing feedback through a vibration to the person sitting on the chair, acknowledgement is sent to the users to correct their body balance. The continuous health status monitoring of the person through real-time database maintenance using mobile application is also the design implementation of the Ergonomic chair. The hip exoskeleton system is a wearable external support to maintain the body posture of human beings suffering from orthopedic difficulties. These types of challenges are faced by the aged and the working people with a sedentary working ambience. The ergonomic chair with an exosuit will encourage good posture for the people with mobility issues. This is a musculoskeletal comfort for the rehabilitation purpose also. This system will also generate the overview of the postures and the activities over a specified period of interval until the person corrects their position.

Specification

Description:
Field of the Invention:
[001] The field of the invention pertains to ergonomic design and human health. Specifically, it focuses on the development of an intelligent seating system aimed at improving human posture and reducing health risks associated with prolonged sitting. This technology integrates advanced ergonomics with data analysis techniques to monitor and correct sitting postures. The invention involves the use of a smart chair equipped with sensors to detect and analyze various sitting postures, employing statistical methods such as ANOVA (Analysis of Variance) to assess and provide feedback on posture correction. The ultimate goal is to enhance user comfort, prevent musculoskeletal issues, and promote better overall health through the optimization of sitting arrangements.

Background of the invention and related prior art:
[002] Prolonged sitting, a common aspect of modern work and study environments, has been linked to various health issues such as poor posture, back pain, and musculoskeletal disorders. Traditional seating solutions often fail to address these problems adequately, leading to discomfort and potential long-term health consequences. With advancements in ergonomics and technology, there is a growing need for innovative seating systems that not only support correct posture but also actively monitor and provide feedback to users. This invention aims to address these challenges by integrating smart technology into chair design, utilizing sensors and data analysis to detect and correct improper sitting postures. By leveraging statistical techniques like ANOVA to analyze posture data, the system offers a proactive approach to improving sitting habits and promoting overall well-being.
[003] In a patent document CA3048254C discloses a ventral support for use in an ergonomic work station chair, the ventral support comprising: a support unit; a Z axis member; and an Y axis member, the support unit including a face, a rear and a top therebetween, the face and the top defining a corner, the face including a right lobe, a left lobe, a clavicles support zone proximate the corner, and a central ridge, which is a sternum support, the central ridge extending vertically between the right lobe and the left lobe, each lobe and the ridge defining a concavity in the face, the Z axis member including a distal end and a proximal end, the proximal end attached to the rear and the distal end attached to the Y axis member.
[004] Another patent JP6478972B2 relates to computer workstations, and more particularly to adjustable workstations that improve an ergonomically beneficial work environment, including prolonged interaction with computer systems and screens. More specifically, the headrest, backrest, seat, largest, armrest, monitor support, input device support, and work tray are coordinated and harmonized through each posture such as a standing posture, a sitting posture, and a reclining posture. ) Relates to an ergonomic workstation having an adjustable chair, monitor, input device support and work tray to ensure operation.
[005] A document US11730269B1 discloses a posture correcting chair having a back rest assembly providing mounting attachments for a head or neck rest, a lumbar support, at least one arm rest, and a posture retainer and supported by a seat assembly. The headrest, lumbar, seat and back support all adjust to allow a user to distribute their weight about a greater number of surfaces for adaptive comfort. A posture retainer affixed to the back rest assembly dynamically adjusts to the contour of a user's body based on force and pressure created while seated to provide active posture correction for a user to prevent slumping or slouching. A knee rest assembly is attached to rail system on a lower end of chair the base platform to provide additional support surfaces. The seat and knee rest assembly include heating, cooling or vibrating or massaging.
[006] Another document KR20210155151A relates to a chair for correcting a posture, comprising: a back unit for supporting a back of a user; a seat unit on which a hip of the user is mounted and which has a cushion; a tilting unit which is provided under the seat unit and tilts the seat unit; and a footrest unit which is fixed and coupled with a front surface of the seat unit in a vertical direction to support a foot of the user. The chair allows the user to maintain a neutral position so as to prevent spinal deformity and conveniently work for a long time.
[007] A patent document US9913541B2 discloses a base with a first end, a second end opposite the first end, and a length extending from the first end to the second end. A frame assembly has a pair of support legs coupled to the base along the length. A seating-support surface is disposed above the base and coupled to the frame assembly. A chest-support surface is disposed above the base and coupled to the frame assembly and the chest-support surface is orientated at an acute angle with respect to the seating-support surface. The pair of the support legs are selectively translatable along the length of the base in a first direction and a second direction opposite the first direction so as to selectively rotate the chest-support surface and the seating-support surface simultaneously while maintaining the acute angle between the chest-support surface and the seating-support surface during the rotation.
[008] None of these above patents, however alone or in combination, disclose the present invention. The invention consists of certain novel features and a combination of parts hereinafter fully described, illustrated in the accompanying drawings, and particularly pointed out in the appended claims, it being understood that various changes in the details may be made without departing from the spirit, or sacrificing any of the advantages of the present invention.

Summary of the invention:
[009] The invention presents a smart chair designed to improve human posture and address health issues associated with prolonged sitting. The chair integrates advanced ergonomic technology with real-time monitoring and feedback systems. It features sensors that track various sitting postures and analyse them using statistical methods, such as ANOVA (Analysis of Variance), to identify improper sitting positions. When incorrect postures are detected, the chair provides feedback through vibrations to prompt users to adjust their position. The system also collects and stores posture data over time to help users understand their sitting habits and make necessary adjustments. The continuous health status monitoring of the person through real-time database maintenance using mobile application is also the design implementation of the Ergonomic chair. This innovative approach aims to enhance user comfort, prevent musculoskeletal disorders, and promote better overall health by encouraging proper sitting techniques.

Detailed description of the invention with accompanying drawings:
[010] For the purpose of facilitating an understanding of the invention, there is illustrated in the accompanying drawing a preferred embodiment thereof, from an inspection of which, when considered in connection with the following description, the invention, its preparation, and many of its advantages should be readily understood and appreciated.
[011] The principal object of the invention is to develop ergonomic sitting arrangement for human posture correction. The invention pertains to a smart chair equipped with advanced ergonomic and monitoring technology designed to enhance posture and prevent health issues associated with prolonged sitting. The chair integrates the following key components and features:
1. Sensor System: The chair is equipped with a network of sensors embedded in the seating area, backrest, and armrests. These sensors measure various parameters such as pressure distribution, weight distribution, and the angle of the body in different planes (frontal and sagittal).
2. Data Acquisition and Analysis: The collected data from these sensors is continuously monitored and recorded. This data is analysed using statistical methods, primarily ANOVA (Analysis of Variance), to assess the sitting postures of the user. ANOVA helps in determining the variance in posture across different sitting conditions and individuals.
3. Feedback Mechanism: When the system detects that a user is sitting in an incorrect posture, it activates a feedback mechanism. This mechanism, typically consisting of vibration motors embedded in the chair, alerts the user to adjust their position. The feedback is designed to be subtle yet effective in encouraging posture correction without being disruptive.
4. Posture Tracking and Reporting: The chair tracks and logs the user's sitting posture over time. This data is used to generate reports and provide insights into the user's sitting habits. Users can review these reports to understand their posture patterns and make adjustments as needed.
5. Adjustment and Customization: The chair may include adjustable components such as seat height, backrest angle, and armrest positions to accommodate different body types and preferences. These adjustments can be synchronized with the monitoring system to provide personalized recommendations for optimal sitting posture.
6. User Interface: An interface, either integrated into the chair or through a connected application, allows users to view their posture data, receive feedback, and customize settings. This interface provides real-time updates and historical data analysis to help users improve their sitting habits.
7. Ergonomic Design: The chair's design adheres to ergonomic principles, ensuring that it supports the natural curves of the body and promotes a healthy sitting posture. The design takes into account factors such as seat depth, lumbar support, and armrest positioning to enhance user comfort and support. The continuous health status monitoring of the person through real-time database maintenance using mobile application is also the design implementation of the ergonomic chair. The hip exoskeleton system is a wearable external support to maintain the body posture of human beings suffering from orthopaedic difficulties. These types of challenges are faced by the aged and the working people with a sedentary working ambience. The ergonomic chair with an exosuit will encourage good posture for the people with mobility issues. This is a musculoskeletal comfort for the rehabilitation purpose also.
By combining these features, the invention provides a comprehensive solution to the problems associated with prolonged sitting. It not only monitors and corrects posture but also offers valuable insights to help users maintain good sitting habits and improve their overall well-being.

Methodology
[012] Data acquisition is the first step towards the posture detection. This step is needed to initiate the process of data analysis of the subject. All data are processed by using ANOVA analysis. Then regression analysis is needed for the precise result using the acquired database regarding different sitting postures during different jobs. Feature extraction is the most important step in this work. For this step, the features are selected which reduce the dimension creating the classification accuracy. This type of feature selection is known as variable selection. In this invention, the regression classification analysis has been performed for feature extraction.
A feature of two or more populations might differ based on multiple factors and ANOVA or analysis of variance which helps to determine whether a significant variation in the feature exists across multiple populations. The feature under test is known as the dependent variable which can vary across multiple populations for a selected independent variable. ANOVA compares the mean of that feature across multiple populations and provides necessary data to conclude if a difference exists for the selected independent variable. In one way ANOVA, a dependent variable of multiple populations is compared for one independent variable whereas in two-way ANOVA more than one independent variable is taken into account. In this analysis, the dependent variable, the weight of sitting posture, is being compared against one independent variable, the different persons, and thus one way ANOVA approach is taken into consideration. The distance between the ground and the chair's sitting area is 45 centimeters. The distance between the ground and the knee Joint of the subject is 49 centimeters and the knee joint to hip joint is 40 centimeters. Here the postures Sitting straight (Center of Pressure Frontal Plane), Sitting straight (Center of Pressure Sagittal Plane), Sitting legs under a chair (Center of Pressure Frontal Plane), Sitting legs under a chair (Center of Pressure Sagittal Plane), Sitting elbows on knees (Center of Pressure Frontal Plane), Sitting elbows on knees (Center of Pressure Sagittal Plane), Sitting elbows on knees with mobile phone (Center of Pressure Frontal Plane), Sitting elbows on knees with mobile phone (Center of Pressure Sagittal Plane) are mentioned as the Sitting posture 1, Sitting posture 2, Sitting posture 3, Sitting posture 4, Sitting posture 5, Sitting posture 6, Sitting posture 7, Sitting posture 8 consecutively.
Table 1: Database acquired from the subjects for different sitting postures


SL. No. Sitting Posture 1 Sitting Posture 2 Weight in Sitting straight Sitting Posture 3 Sitting Posture 4 Weight in Sitting legs under a chair Weight Sitting Posture 5 Sitting Posture 6 Weight in Sitting elbows on knees Sitting Posture 7 Sitting Posture 8 Weight in Sitting elbows on knees with mobile phone
1 40.45 -33.97 30.2 35.86 50.62 34.2 90.84 75.45 12.4 83.18 65.96 11.65
2 38.8 -8.93 21.3 38.69 111.53 26.7 139.59 102.01 9.2 135.85 99.61 8.2
3 25.76 -19.23 30.4 24.68 12.52 30.2 72.44 87.12 13.3 72.06 76.96 12.65
4 38.32 47.78 28 32.55 101.04 33.55 61.45 129.22 18.3 53.13 129.44 19.35
5 53.85 47.14 10.1 124.62 92.39 12.8 221.93 154.84 5.25 221.88 154.79 6.1
6 7.34 -55.87 16.5 57.65 63.04 22.4 25.88 29.1 5.1 0 12.5 4.65
7 51.38 47.29 19.7 49.38 130.49 22.95 163.79 163.76 11.95 155.91 162.97 12.7
8 76.45 69.43 25.6 54.59 141.08 34.6 117.18 109.08 15.5 118.43 110.97 14.75
9 21.23 -26.77 33.1 8.31 86.6 43.5 50.22 55.62 17 25.34 -10.96 27.5
10 7.3 -15.76 61.8 14.75 59.13 70.4 5.32 29.38 39.8 35.13 -63.6 53.25
11 23.45 -14.48 43.3 15.63 77.17 45.2 51.34 89.88 22 48.17 89.7 21
12 20.01 -40.55 46.75 31.26 35.57 51 49.07 -16.36 26.2 59.75 -18.71 23
13 29.48 -37.37 40.25 15.73 68.77 53.25 52.17 -3.98 18.65 29.3 -64.64 29.75
14 74.42 76.5 34.7 46.25 118.68 43.2 117.29 140.34 17.4 126.95 143.15 16.9
15 66.39 -14.6 35 56.36 93.56 45.1 89.93 72.96 16.3 102.71 16.38 17.65
16 12.16 -23.93 57.5 0.01 32.87 67 20.9 55.95 40.6 17.52 40.78 39.5
17 8.66 17.63 60.6 1.07 5.84 69.7 4.06 38.65 51.3 3 53.51 45.3
18 28.29 -53.71 27.9 21.61 -9.83 26.3 29.95 -11.5 16.6 22.23 -27.74 17.2
19 35.71 17.1 37.5 34.28 72.99 41.25 91.02 17.27 27 86.68 67.23 24.6
20 25.83 36.69 19.8 25.47 98.36 21.5 101.93 77.81 8.42 135.41 99.23 7.2
21 43.76 35.98 5.3 116.39 154.63 17.3 0 12.5 3.25 110.67 78.67 5.35
22 29.13 -80.1 25.6 40.55 130.21 33.4 24.84 -48.9 13.2 6.06 -47.93 11.75
23 42.31 -33.09 43.5 38.31 46.85 57.1 84.48 78.01 25.55 88.39 71.08 24.4
24 24.05 42.79 19 42.85 127.89 25 221.87 154.65 7.2 221.75 154.57 6.9
25 36.7 -21.63 18.2 22.49 128.92 31 164.82 118.13 7.2 169.05 120.86 6.95
26 -29.66 -111.42 13.3 54.42 56.59 16 0 12.5 2.9 0 12.5 3
[013] Here 19 no of subjects have been involved and among them 10 are males and 9 are female to acquire the data of postures. For the experiment, the age of all the subjects is between 16 to 50 years. The subjects are showing different 8 types of postures in sitting position. Weight measurements from body part of the subjects are collected and used for the system behavior analysis. Force values are compared with the weight (kg) of the subjects. For pressure force, the value from frontal and sagittal plane are considered. Most effective instruments and systems are used to obtain all the data from subjects. In the present work, MBN 'stabilo' force platform is used to collect the data. This platform is installed into the chair and the objects are sitting in different postures and then the values are observed and collected. The sitting area is (380*360) mm-square. The frontal and sagittal planes are playing a vital role to recognize the health status in musculoskeletal system. So, in these 8 types of different postures in sitting position the values of frontal and sagittal pressures are observed. These observed values are compared with the weights of the subject. By the help of these comparison values the wrong posture of the subjects are detected.

Results & discussions

Table 2: ANOVA analysis of the subject for different sitting postures

Sl. No. Name of the Postures Sum of Squares (SS)
(Model) Sum of Squares (SS)
(Error) Sum of Squares (SS)
(Total) Mean Square (MS)
[SS(Model)/ (m-1)] Mean Square Error (MSE)
[SS(Error)/ (n-m)] F Value

= (MS/MSE) Prob>F
1 Sitting straight (Center of Pressure Frontal Plane) 454.64912 12254.27266 12708.92179 454.64912 510.59469 0.89043 0.35476
2 Sitting straight (Center of Pressure Sagittal Plane) 717.45211 53874.67075 54592.12286 717.45211 2244.77795 0.31961 0.57709
3 Sitting legs under a chair (Center of Pressure Frontal Plane) 8913.04669 12384.29452 21297.34122 8913.04669 516.01227 17.27294 3.54931E-4
4 Sitting legs under a chair (Center of Pressure Sagittal Plane) 9014.69634 39425.98273 48440.67907 9014.69634 1642.74928
5.48757 0.02778
5 Sitting elbows on knees (Center of Pressure Frontal Plane) 17622.52039 83950.89126 101573.41165 17622.52039 3497.9538 5.03795 0.03428
6 Sitting elbows on knees (Center of Pressure Sagittal Plane) 4733.86523 80050.62597 84784.4912 4733.86523 3335.44275 1.41926 0.24517
7 Sitting elbows on knees with mobile phone (Center of Pressure Frontal Plane) 23612.69838 82881.07053 106493.76891 23612.69838 3453.37794 6.83757 0.01518
8 Sitting elbows on knees with mobile phone (Center of Pressure Sagittal Plane) 23833.22185 95748.17489 119581.39674 23833.22185 3989.50729 5.97398 0.02224
9 Sitting straight (Center of Pressure Sagittal Plane) 717.45211 53874.67075 54592.12286 717.45211 2244.77795 0.31961 0.57709


[014] ANOVA analysis means the variance analysis of any dataset. In this work, ANOVA calculation has been performed for the eight types of different postures in sitting position using acquired database. It is a statistical technique used in the present work. ANOVA is used to predict the posture of sitting by observing the statistical values such as mean value difference from one sitting condition parameter to another. From the above Table 2 some of the features such as Sum of Squares (SS), Mean Square (MS), Mean Square Error (MSE), F Value and prob>F are achieved using Origin software. Sum of Squares (SS) is the addition of each Squared Deviation (SD) of the parameters. SS is calculated by a formula, SS= ∑x2 - {(∑X) 2 /N} [where, N is the total number of data; (∑X) is summation of total average or mean values and then calculate the square of total mean value i.e. (∑X) 2; ∑x2 is the summation of square value of individual data. When the subjects are in Sitting straight Center of Pressure Frontal Plane, the total SS value is 12708.92179 and this is the minimum total SS value from the objects. In the sitting straight Center of Pressure Sagittal Plane position, the total SS is 54592.12286. At the same way in the other sitting position got the total SS values. The maximum value of total SS is observed in sitting elbows on knees with mobile phone Center of Pressure Sagittal Plane position and the value is 119581.39674. Degree of Freedom is also calculated by three steps. As total numbers of data are N, eight types of different poses on sitting position are used i.e. m, so Degree of Freedom (DF Model) = (m-1) = (8-1) =7 and Error of DF= (N-m) get MS = (26-8) =18. These DF values are same for all the sitting positions. Mean Square (MS) is the division of (SS Modal) by (DF Model) i.e. MS Model = {SS/ (m-1)}. In this present work, using this formula MS values are achieved respectively in eight types of different poses in sitting position and the values are respectively 454.64912, 717.45211, 8913.04669, 9014.69634, 17622.52039, 4733.86523, 23612.69838 and 23833.22185. Mean Square Error (MSE) has been calculated same as MS Model i.e. MSE or MS Error= {SS/ (N-m)}. The max. MSE value is observed when the subjects are sitting elbows on knees with mobile phone Center of Pressure Sagittal Plane position and the value is 3989.50729. The min. value of MSE is shown in the position of sitting straight Center of Pressure Frontal Plane and i.e. 510.59469. The F value means the ratio between to mean square values which depends on null hypothesis. F value is calculated by using a formula i.e. F = (MS Model / MSE or MS Error) and the values are achieved respectively 0.89043, 0.31961, 17.27294, 5.48757, 5.03795, 1.41926, 6.83757 & 5.97398 in all the sitting positions. Observing three true null hypothesis values in the table when the subjects are sitting on the positions respectively sitting straight Center of Pressure Frontal Plane, sitting straight Center of Pressure Sagittal Plane & Sitting legs under a chair Center of Pressure Sagittal Plane. In these three positions the value of F is near to 1 and these values are satisfied the true null hypothesis formula i.e. F value>1. This true null hypothesis depends on the P value or Probability value of F. If the P<0.05 (a common alpha level value for the test), then this null hypothesis can be rejected. But in this recent work, three values are significant statistical values because these three values are presented P>0.05 values in three different sitting positions and the values are respectively 0.35476, 0.57709 & 0.02778. Rest of the five values in five different sitting positions are satisfied the formula for the rejection of true null hypothesis i.e. P>0.05. So, these null hypotheses are can be rejected. This type of analysis is required for the better prediction in research work.

Table3: Statistical Output of the subject for different sitting postures

Sl. No. Name of the Posture
SD (Standard Deviation) SEM (Std. Error of Mean) Mean Median Adjacent R-Square RMS RMS Error
1 Sitting straight (Center of Pressure Frontal Plane) 22.54677 4.42179 31.98346 29.305 -0.0044 21.32250 22.59634
2 (Sitting straight Center of Pressure Sagittal Plane) 46.72991 9.16449 -5.88769 -15.18 -0.02798 26.78529 47.37909
3 Sitting legs under a chair (Center of Pressure Frontal Plane) 29.18722 5.72408 38.60615 35.07 0.39428 94.40893 22.71590
4 Sitting legs under a chair (Center of Pressure Sagittal Plane) 44.01849 8.63274 80.28885 81.885 0.15219 94.94575 40.53084
5 Sitting elbows on knees (Center of Pressure Frontal Plane) 63.74117 12.50067 78.935 66.945 0.13906 132.74984 59.14350
6 Sitting elbows on knees (Center of Pressure Sagittal Plane) 58.23555 11.42093 66.28808 74.205 0.01649 68.80309 57.75329
7 Sitting elbows on knees with mobile phone (Center of Pressure Frontal Plane) 65.26677 12.79987 81.86731 77.62 0.1893 153.66424 58.76544
8 Sitting elbows on knees with mobile phone (Center of Pressure Sagittal Plane) 69.16109 13.5636 58.74154 69.155 0.16594 154.38012 63.16254

[015] In this data analysis, the statistical values of SD, SEM, Mean, Median, Adj. R-Square, RMS & RMS Error are used to detect the right posture with the accuracy. According to the rule of Thumb, the value of Adj. R-Square is more than 0.75 is accurate value and 0.4 is the acceptable value for comparison and prediction. Root Mean Square Error is a better index for accurate value in comparison with the predicted values. RMSE value is equal and greater than 0.5. The smallest mean value i.e. 31.98346 is observed in the sitting straight center of pressure frontal plane position. The highest mean value i.e. 81.86731 is observed in sitting elbows on knees with mobile phone center of pressure frontal plane. The Table 2 shows that the mean values are changing according to the various poses of the subjects. The minimum mean value became fixed when the elbows on knees and maximum values are fixed in sitting legs under a chair. The lowest Adj. R-Square value i.e. 0.01649 is observed in sitting elbows on knees center of pressure sagittal plane position and highest Adj. R-Square value i.e. 0.39428 is observed in sitting legs under a chair center of pressure frontal plane position. In the work, the values are collected from male and female volunteers with different body weights. So that mean values, standard deviation, RMS, RMSE and other coefficient variant show high values in different positions. These values indicate that the relationship between postures in the chair depends on their weight and other body parameters.
[016] The linear regression analysis is used to predict the wrong posture according to the changes of mean values and other parameters. Using this method, some regression equations and values. In the relationship between sitting straight and sitting legs under a chair with weight measurements, the value 3.3757 has been observed. In the graphical representations of sitting elbows on knees (kg) with respect to the sitting elbows on knees position, the value -6.5347. ANOVA or analysis of variance is a Statistical method that allow us to determine if average value of three or more population is different than each other or not. For example, if sales of a product are dependent upon location or if performance of students varies as per different subjects and etc.
In ANOVA, the feature for which the analysis of difference needs to be calculated is known as the Dependent variable. For example, the sales of a product or the marks of the students. On the other hand, the categories or the groups for which a difference might exists are called Independent Variables. For example, the varying location, or the different subjects. In general, a T Test/Matched Test can be used while comparing the dependent variables of only two populations for one particular independent variable. But most of the time this difference is analyzed for more than two population and the T/Matched tests can become pretty tedious. Therefore, in these situations analysis of variance or ANOVA approach is followed as it provides a very efficient and quick way to determine if a significant variance exists in the dependent variable for more than two populations for a fixed independent variable. When only one independent variable is taken into account (for example the scores based on subjects) it is called as One Way ANOVA. More than one independent variable (for example score based on subjects and grades) will require us to follow the two-way ANOVA method.
[017] The digital goniometer will give the information of the angular movement between the lower limb specially the thigh portion and the dorsal part specially the back of the human being. If the person is moving little bit forward then the center of mass is at the same position but the new position can be detected through ultrasonic sensor and the digital goniometer placement. The mobile application will track the health status of the employees and give the recommendation of the exercises. The recommendation system is incorporated due to of the sedentary employees who may suffer from the different types of possible diseases such as cervical spine issues etc. This is the future idea of the ergonomically designed smart chair.

Table 4: Information about the prediction and Recommendation regarding wrong posture in the working hours

SL. No. Angle of Bending (degree) Time duration spent (hours) Health Issue predicted for Wrong posture Recommended Exercise
1 45 7-8 Back Pain Isometric Rows
2 120 7-8 Back Pain Isometric Rows
3 135 7-8 Back Pain Isometric Rows

Figure 1. Schematic diagram of the output prediction of sitting postures according to the embodiment of the present invention.
Figure 2. Sitting straight according to the embodiment of the present invention.
Figure 3. Sitting legs under a chair according to the embodiment of the present invention.
Figure 4. Sitting elbows on knees according to the embodiment of the present invention.
Figure 5. Sitting elbows on knees with mobile phone according to the embodiment of the present invention.
Figure 6. Graphical representation of sitting straight center of pressure frontal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 7. Graphical representation of sitting straight center of pressure sagittal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 8. Graphical representation of sitting under a chair center of pressure frontal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 9. Graphical representation of sitting under a chair center of pressure sagittal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 10. Graphical representation of sitting elbows on knees center of pressure frontal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 11. Graphical representation of sitting elbows on knees center of pressure sagittal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 12. Graphical representation of sitting elbows on knees with mobile center of pressure sagittal plane w.r.t. sitting straight weight according to the embodiment of the present invention.
Figure 13. Techno-commercial hardware setup according to the embodiment of the present invention.
[018] Without further elaboration, the foregoing will so fully illustrate my invention, that others may, by applying current of future knowledge, readily adapt the same for use under various conditions of service. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the invention.

Advantages over the prior art
[019] Ergonomic sitting arrangement for human posture correction proposed by the present invention has the following advantages over the prior art:
1. Improved Posture: By providing real-time feedback on sitting posture, the smart chair helps users maintain correct posture, reducing the risk of developing musculoskeletal disorders and back pain.
2. Health Prevention: Regular use of the chair can prevent long-term health issues associated with poor sitting habits, such as spinal deformities and repetitive strain injuries.
3. Personalized Feedback: The chair's ability to monitor and analyse individual sitting patterns allows for personalized feedback and recommendations, tailored to the specific needs and habits of each user.
4. Data-Driven Insights: The system collects and analyses posture data over time, providing users with valuable insights into their sitting habits and trends, which can be used to make informed adjustments and improvements.
5. Increased Comfort: Ergonomic design features, combined with adjustable components, ensure that the chair provides optimal comfort and support for a wide range of body types and preferences.
6. Proactive Posture Correction: The vibration feedback mechanism offers immediate alerts to users, encouraging them to correct their posture before discomfort or health issues arise.
7. Enhanced Productivity: By promoting better posture and reducing discomfort, the chair can help improve concentration and productivity, as users are less likely to experience discomfort that can disrupt their work or study.
8. Long-Term Benefits: Consistent use of the smart chair can lead to long-term improvements in posture and overall health, contributing to a better quality of life and reduced healthcare costs related to posture-related conditions.
[020] In the preceding specification, the invention has been described with reference to specific exemplary embodiments thereof. It will be evident that various modifications and changes may be made thereunto without departing from the broader spirit and scope of the invention as set forth in the claims that follow. The specification and drawings are accordingly to be regarded in an illustrative rather than restrictive sense. Therefore, the aim in the appended claims is to cover all such changes and modifications as fall within the true spirit and scope of the invention. The matter set forth in the foregoing description and accompanying drawings is offered by way of illustration only and not as a limitation. The actual scope of the invention is intended to be defined in the following claims when viewed in their proper perspective based on the prior art.



, Claims:We claim:
1. Ergonomic sitting arrangement for human posture correction which consists of:
- a sensor system integrated into the chair to measure pressure distribution, weight distribution, and body angle in frontal and sagittal planes;
- a data acquisition module that collects and records sensor data;
- a data analysis unit configured to analyse the collected data using ANOVA (Analysis of Variance) to assess and identify incorrect sitting postures;
- a feedback mechanism that provides a corrective signal, such as vibration, when an incorrect posture is detected;
- a user interface that displays posture data and feedback to the user and allows for customization of chair settings.
2. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the feedback mechanism includes vibration motors embedded in the seating area, backrest, and armrests of the chair.
3. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the data acquisition module logs posture data over time to generate detailed reports and insights into the user's sitting habits.
4. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the data analysis unit employs regression analysis for feature extraction and accurate prediction of posture-related issues.
5. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the chair's ergonomic design includes adjustable components such as seat height, backrest angle, and armrest positions, which can be synchronized with the monitoring system to provide personalized posture recommendations.
6. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the user interface is provided through a built-in display or a connected application that allows users to view real-time posture data and historical trends.
7. Ergonomic sitting arrangement for human posture correction as claimed in claim 1 wherein the system is capable of performing one-way or two-way ANOVA to compare posture data across different sitting conditions or user groups.
8. A method for improving sitting posture using the smart chair of claim 1, comprising:
- monitoring sitting posture with the sensor system;
- analysing posture data using the data analysis unit to detect incorrect postures;
- providing corrective feedback through the feedback mechanism;
- generating and displaying reports on posture habits and recommendations through the user interface.
9. The method of claim 8, wherein the corrective feedback includes vibration alerts that prompt users to adjust their sitting posture.
10. The method of claim 8, wherein the data analysis includes generating statistical reports based on ANOVA and regression analysis to identify and address posture-related issues.

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