Ageing and neurodegenerative disorders

Editoria

Alzheimer's patient activity assessment using different sensors

International audiencePurpose: Older people population is expected to grow dramatically over the next 20 years (including Alzheimer's patients), while the number of people able to provide care will decrease. We present the development of medical and information and communication technologies to support the diagnosis and evaluation of dementia progress in early stage Alzheimer disease (AD) patients.Method: We compared video and accelerometers activity assessment for the estimation of older people performance in instrumental activities of daily living (IADL) and physical tests in the clinical protocol developed by the Memory Center of the Nice Hospital and the Department of Neurology at National Cheng Kung University Hospital - Taiwan. This clinical protocol defines a set of IADLs (e.g., preparing coffee, watching TV) that could provide objective information about dementia symptoms and be realistically achieved in the two sites observation room. Previous works studied accelerometers activity assessment for the detection of changes in older people gait patterns caused by dementia progress, or video-based event detection for personal self-care activities (ADLs)[1, 2, 3], but none has used both sensors for IADLs analysis. The proposed system uses a constraint-based ontology to model and detect events based on different sensors readings (e.g., 2D video stream data is converted to 3D geometric information that is combined with a priori semantic information, like defined spatial zones or posture estimations given by accelerometer). The ontology language is declarative and intuitive (as it uses natural terminology), allowing medical experts to define and modify the IADL models. The proposed system was tested with 44 participants (healthy=21, AD=23). A stride detection algorithm was developed by the Taiwanese team for the automatic acquisition of patients gait parameters (e.g., stride length, stride frequency) using a tri-axial accelerometer embedded in a wearable device. It was tested with 33 participants (healthy=17, Alzheimer = 16) during a 40 meters walking test. Results & Discussion: The proposed system detected the full set of activities of the first part of our clinical protocol (e.g., repeated transfer test, walking test) with a true positive rate of 96.9 % to 100%. Extracted gait parameters and automatically detected IADLs will be future analyzed for the evaluation of differences between Alzheimer patients at mild to moderate stages and healthy control participants, and for the monitoring of patients motor and cognitive abilities

Tackling challenges in care of Alzheimer's disease and other dementias amid the COVID-19 pandemic, now and in the future

We have provided an overview on the profound impact of COVID-19 upon older people with Alzheimer's disease and other dementias and the challenges encountered in our management of dementia in different health-care settings, including hospital, outpatient, care homes, and the community during the COVID-19 pandemic. We have also proposed a conceptual framework and practical suggestions for health-care providers in tackling these challenges, which can also apply to the care of older people in general, with or without other neurological diseases, such as stroke or parkinsonism. We believe this review will provide strategic directions and set standards for health-care leaders in dementia, including governmental bodies around the world in coordinating emergency response plans for protecting and caring for older people with dementia amid the COIVD-19 outbreak, which is likely to continue at varying severity in different regions around the world in the medium term

The feasibility and practicality of auxiliary detection of spatial navigation impairment in patients with mild cognitive impairment due to Alzheimer's disease by using virtual reality

Background: Spatial disorientation in patients with mild cognitive impairment due to Alzheimer's disease (MCI due to AD) has become a subject of great interest. Medical practitioners are concerned about the serious issue of these patients who are getting lost. Therefore, the early detection of MCI due to AD is crucial. New methods: We designed virtual reality (VR) protocols to test spatial recognition abilities. Our devices mainly included the Vive Pro Eye and the Steam VR program. We tested the three groups: young cognitively unimpaired (YCU), older cognitively unimpaired (OCU) and MCI due to AD. We also administered the Cognitive Abilities Screening Instrument and the Questionnaire on Everyday Navigational Ability for comparison. Results: We adopted the testing results of 2 YCU, 3 OCU, and 4 MCI due to AD for analysis. Concerning cognitive abilities, YCU and OCU had better performance than MCI due to AD respectively. It was consistent with the recent memory and the total scores of the Cognitive Abilities Screening Instrument. Comparison with existing methods: We introduced a real-life setting, the Tzu-Chiang campus at National Cheng Kung University, into the VR environment. It allowed us to assess daily road-recognizing abilities of participants in a controlled testing environment. Conclusions: Several limitations were considered in this study, such as limited number of participants and low-quality images on the screen. Nonetheless, this device has the potential to serve as a screening tool for MCI due to AD based on its feasibility and practicality

The Incidence and Recurrence of Getting Lost in Community-Dwelling People with Alzheimer’s Disease: A Two and a Half-Year Follow-Up

<div><p>Getting lost (GL) is a serious problem for people living with Alzheimer’s disease (PwAD), causing psychological distress in both PwAD and caregivers, and increasing the odds of being institutionalized. It is thus important to identify risk factors for the GL events in PwAD. Between April 2009 and March 2012, we invited 185 community-dwelling PwAD and their caregivers to participate in this study. At the baseline, 95 had experienced GL (Group B); the remaining 90 (Group A) had not. We focused on the incidence of GL events and the associated factors by way of demographic data, cognitive function assessed by the Cognitive Ability Screening Instrument (CASI), and spatial navigation abilities as assessed by the Questionnaire of Everyday Navigational Ability (QuENA). After a 2.5-year period, the incidence of GL in Group A was 33.3% and the recurrence of GL in Group B was 40%. Multiple logistic regression analysis revealed that the inattention item on the QuENA and orientation item on the CASI had independent effects on the GL incidence, while the absence of a safety range was associated with the risk of GL recurrence. During the 2.5 years, the PwAD with GL incidence deteriorated more in the mental manipulation item on the CASI than those without. We suggest that before the occurrence of GL, the caregivers of PwAD should refer to the results of cognitive assessment and navigation ability evaluation to enhance the orientation and attention of the PwAD. Once GL occurs, the caregivers must set a safety range to prevent GL recurrence, especially for younger people.</p></div

Flow chart of the study participants and Groups.

<p>Abbreviation: AD = Alzheimer’s disease; QuENA = Questionnaire of Everyday Navigational Ability; GL = getting lost.</p

The predictive power of variables of interest for new GL ocurrence^*.

<p>The predictive power of variables of interest for new GL ocurrence^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155480#t002fn003" target="_blank">*</a>}.</p

Predictors of getting lost.

<p>Predictors of getting lost.</p

Independent effects of predictors for new GL occurrence^*.

<p>Independent effects of predictors for new GL occurrence^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155480#t003fn004" target="_blank">*</a>}.</p

Deterioration in neuropsychological test^*.

<p>Deterioration in neuropsychological test^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155480#t004fn002" target="_blank">*</a>}.</p