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System and Method for Improved Ergonomic Chair Using Ergonomic-Data Classification and Cognition, Analytics, and Learning

IP.com Disclosure Number: IPCOM000243682D
Publication Date: 2015-Oct-09
Document File: 6 page(s) / 98K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a network-connected auto-adjusting smart chair with local sensors and Cloud/server-based analytics and data storage. The system is applicable to any user and to chairs in public locations, as opposed to current high-end ergonomic chairs that are designed for private use. Personalization is based on measurement, learning, and leveraging similar previous usersâ?T settings across multiple chairs as well as site information and other available information.

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System and Method for Improved Ergonomic Chair Using Ergonomic - ,

Analytics

Analytics ,

High end ergonomic chairs allow the user to make many adjustments . When purchased for private use, the user adjusts the chair according to the instructions provided; usually, the user only needs to do this one time. As only one person sits in the chair, it rarely requires readjustments. In a public space, such as conference room, doctor's office, airport lounge for frequent flyers, etc., setting the position of the chair to meet individual ergonomic needs becomes a problem if the user is not familiar with the chair settings/options.

A system is needed to provide situation aware automated adjustment of smart chairs in public locations.

The novel contribution is a network connected smart chair with local sensors and cloud/server based analytics, which can automatically adjust the settings for any user. The system is applicable to chairs in public locations, as opposed to current high end ergonomic chairs that are designed for private use. The novel system provides automatic chair setting adjustments for different users in different situations . The personalization is based on measurement, learning, and leveraging similar previous users' settings across multiple chairs as well as site information and other possibly available information. The information is stored in Cloud and is remotely accessible .

The system is comprised of analytics and cloud computing components . It is equipped

with sensors to measure user's dimensions in lieu of profile information . The chair system communicates with the user's personal device (e.g., smart phone, tablet, etc.) over Bluetooth* and other protocols, to read the customer/user profile. The profile for use by cognitive chairs includes the user's physical metrics, medical status, etc.

The system uses a fingerprint reader type of credential input mechanism to access profile information, as well as any previously successful chair settings. The chair uses cloud based analytics to determine the ideal settings for the current user's profile . Supervised machine learning models allow the system to create the ideal settings for different user profile dimensions. Based on user feedback, the system receives continuous retraining for readjustments upon use .

Figure: Architecture

-Data

Data

Classification and Cognition , ,

and Learning

and Learning

1


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The chair system can communicate with the user's smart device (e.g., via a device receptacle) to load profile information as the user permits . Profile information includes (but is not limited to):


• Physical metrics: height, weight, other dimensions such as shoulder, hip, waist, inseam and other measurements


• Medical status (suitably sanitized): back problem, arthritis, pregnancy

The chair contains sensors to automatically derive an approximate measurement of the user's body dimensions if no software profile is available . An industry standard for storing...