Advances in applying somatosensory interaction technology in geriatric care:A bibliometric analysis

Objectives:Somatosensory Interaction Technology(SIT)is used in various aspects of geriatric care.We aimed to conduct a bibliometric analysis to summarize relevant publications and visualize publication characteristics,current hotspots,and development trends,thereby inspiring subsequent researches.Methods:We searched theWeb of Science Core Collection database for publications on the application of SIT in geriatric care.Bibliometric visualization and clustering analysis were performed using VOSviewer V1.6.18 Software,while keywords burst detection analysis was conducted with CiteSpace 6.1.R6 Software.Results:After screening,a total of 1,019 publications were included.The number of publications on SIT in geriatric care is gradually increasing,exhibiting a rapid growth rate.The United States,Canada,and Australia led in terms of publication volume.Keyword clustering analysis identified major research hotspots:crisis warning,somatic abilities,rehabilitation training and psychosocial support.Initial studies primarily explored themes such as recovery,movement,systems,and later shifted towards gait analysis,muscle strength,parameters,and home-based care.More recently,research themes have evolved to dementia,machine learning,and gamification.Conclusions:SIT is innovative for promoting active aging,advancing intelligent healthcare,and elevating the daily quality of life for older adults in clinical and domestic settings.Applications of SIT can be categorized into early warning systems for crises,detailed analyses of physical conditions,rehabilitation enhancement,and support for psychosocial health.Research trends have transitioned from whole-body recognition to precise feedback,from a focus on physical health to mental health,and from technical feasibility to user-friendliness.Future research should focus on developing accessible and user-friendly devices,fostering interdisciplinary collaborations for innovation,expanding research to address both the physical and mental health needs of diverse older adults,and integrating emerging technologies to enhance data precision and accelerate the development of intelligent platforms.

Advances in caring for the older cancer patient：a report from the 2015 conference of the International Society of Geriatric Oncology

A paradox in cancer research is that the majority of patients enrolled in clinical trials are relatively young and fit while typical patients in daily practice are elderly and have comorbidities and impaired organ function. Given these differences, many major studies provide an imperfect guide to optimizing the treatment of the majority of patients. Since cancer incidence is highly correlated with age, and since the world's population is rapidly ageing, this problem can only increase. For this reason, oncologists and geriatricians need to collaborate in developing tools to systematically assess the health status of elderly patients and their fitness to receive cancer therapies of various intensity. Tailoring anti-cancer treatments and supportive care to individual needs should be seen as part of the move towards personalized medicine. Achieving this goal is as much of a challenge to developing and middle-income countries as it is to western nations. The 2015 annual conference of the International Society of Geriatric Oncology(SIOG) held in Prague, Czech Republic, November 2015 and had a global focus on advancing the science of geriatric oncology and supportive care. Central to this approach is the systematic assessment of life expectancy, independent functioning, and the physical and psychological health of older cancer patients. The assumption behind comprehensive geriatric assessment is that elderly cancer patients have complex needs. The implication is that effective intervention will require a multidisciplinary team. Examples of effective geriatric assessment, multidisciplinary working and supportive care were presented at the SIOG conference.

Shanghai Institutional Caring for Labor Force Demand Forecasting Based on GM （1,1） Model

As a city with the most aging population in China, a well-established elderly care system is of great importance. Based on the modeling mechanism of GM （ 1.1 ） model, this paper establishes a demand forecast model of elderly care labor force in Shanghai and applies gray prediction GM （1.1） model, taking the data of elderly care services in Shanghai from 2009 to 2015 as the basis, solving the model to get the forecast value of the gearing demand for geriatric care workers, and comparing the actual value with the predicted value. The test results show that the model predictive value Better, higher accuracy, less error rate. Using this model, we can get the forecast value of the elderly care labor force in Shanghai from 2009 to 2015, which provides the basis for the Shanghai elderly care labor force development plan.