Systematic review of recent years: machine learning-based interactive therapy for people suffering from dementia

Medical advances over the last century have significantly extended life expectancy. Today, the world's population is quite old, and will become even older in the years to come. Diseases that particularly concern the elderly are therefore more frequent, and dementia is one of them. This condition mainly affects the elderly and cannot be cured today. However, people suffering from dementia do require care, and this entails significant costs for our society. Machine learning could be useful in a context where it is difficult to find medical staff and where cost reduction is a priority. In recent years, research has been conducted to find ways of treating dementia with machine learning-based therapies in which the patient can actively participate. In this paper, a systematic literature review of these therapies is conducted: (a) paper metadata is analysed, (b) dataset characteristics are examined, (c) therapy types are compared, (d) suggested architectures are considered, (e) therapy performance is reviewed, (f) usability is discussed, and g) ethical considerations are taken into account. Twenty-three papers were selected in which various types of therapy were suggested for use with cell phones, computers, robots, or virtual reality. The results of the usability tests were very positive, both in terms of cognitive faculties evolution and patient satisfaction.