## 7 Conclusions  
This study starts from the fundamental interaction of information reception, identifies the difficulties that may exist in the information reception of elderly users, introduces the ability-needs matching method, and establishes a systematic and complete ability-needs matching method for FCM. The study of elderly users' life abilities is transformed into the study of three types of abilities: perception, cognition, and execution. The needs of elderly users are profoundly analysed, the existing home product functions are quantified in a gradient to match them, and finally, the relevant inner matching demand pattern is derived, which completes the auxiliary elderly users' behaviour and establishes iterative data integration.  
1. The FCM home product function-life ability matching method can be understood as a matching relationship between the user ability gradient and product demand level.
2. The FCM home product function-living ability matching method links user needs (physiological needs, psychological needs, actual needs, hidden needs), user abilities (cognitive ability, perceptual ability, execution ability), and studies user behaviour in the user living environment, to design an intelligent home system for the user that meets the user's needs.
3. After analysis, the ability range of senior living is divided into three adaptation ranges: ability surplus range (SR), ability matching range (MR), and ability lacking range (IR).
4. The intelligent functions of age-friendly furniture can be split into four design elements: intelligent recognition function, intelligent adjustment function, intelligent monitoring function, and intelligent prompting function under the theoretical guidance of the FCM home product function-life ability matching model.
5. The advantages of the FCM approach are highlighted at the designer, production, and user levels. The FCM model focuses on the connection between the user's environment, the user's demand for home product functions, and the user's ability to live.  
**Author Contributions:** [PERSON] contributed to data curation, funding acquisition, and writing--review and editing. [PERSON] contributed to data curation, methodology, visualization, and writing--original draft. [PERSON] contributed to visualization. [PERSON] contributed to writing--review and editing. All authors have read and agreed to the published version of the manuscript.  
Part of this work was supported by the National Key Research and Development Program (2017 YFD0601104), and part of it was supported by the 2020 Jiangsu Postgraduate \"International Smart Health Furniture Design and Engineering\" project, and 2022 Jiangsu Province Ecological Health Home Furnishing Industry-University-Research International Cooperation Joint Support for laboratory projects. Part of this work was also sponsored by Qing Lan Project.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patients to publish this paper. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Nanjing Forestry University.  
This work applicable.  
Thanks for the research technical and ErgoLAB Man-Machine-Environment Testing Cloud Platform (ErgoLAB v3.0) related scientific research equipment support of the Kingfar project team.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
IoT Internet of Things