Sensor-based surveillance technology (SST) is increasingly employed in the care of people with dementia (PwD) in hospitals, nursing homes, and home care. With improved functionality and availability of SST, there will likely be a growing utilization in clinical settings. In the context of staff shortage, the expected resource-efficient safety benefits are attractive but must be critically balanced against concerns that basic ethical principles are violated. In this discussion paper, we provide a brief overview of frequently used SST and discuss ethical issues associated with their use. We identify intrusion into privacy and the complex interaction between stakeholders as the biggest challenges. Moreover, the frequent lack of decision-making capacity in PwD poses particular ethical challenges. Evidence concerning safety benefits exists mostly for the detection of patients leaving the intended area (i.e., getting up, leaving the premises) or occurring falls. The level of privacy intrusion to detect occurring falls varies widely between different sensor systems. Finally, we propose best practice recommendations for the clinical implementation of SST in the care of PwD, and we address the circumstances under which the use of sensors can be ethically justified despite the absence of legally valid informed consent.

Gait abnormalities in older adults are linked to increased risks of falls, institutionalization, and mortality, necessitating accurate and frequent gait assessments beyond traditional clinical settings. Current methods, such as pressure-sensitive walkways, often lack the continuous natural environment monitoring needed to understand an individual’s gait fully during their daily activities. To address this gap, we present a Lidar-based method capable of unobtrusively and continuously tracking human leg movements in diverse home-like environments, aiming to match the accuracy of a clinical reference measurement system. We developed a calibration-free step extraction algorithm based on mathematical morphology to realize Lidar-based gait analysis. Clinical gait parameters of 45 healthy individuals were measured using Lidar and reference systems (a pressure-sensitive walkway and a video recording system). Each participant participated in three predefined ambulation experiments by walking over the walkway. We observed linear relationships with strong positive correlations ($R^2>0.9$) between the values of the gait parameters (step and stride length, step and stride time, cadence, and velocity) measured with the Lidar sensors and the pressure-sensitive walkway reference system. Moreover, the lower and upper 95% confidence intervals of all gait parameters were tight. The proposed algorithm can accurately derive gait parameters from Lidar data captured in home-like environments, with a performance not significantly less accurate than clinical reference systems.

Thyroid dysfunction is a common adverse event during pembrolizumab therapy, but severe hypothyroidism accompanied by acute neuropsychiatric symptoms is rare. We present the case of a 78-year-old woman with metastatic colorectal cancer who developed agitation, hallucinations, and confusion three months after initiation of Pembrolizumab. Evaluation revealed profound hypothyroidism (TSH 37.9 mU/L, free T3 <0.60 pmol/L and free T4 <0.5 pmol/L) and moderate hyponatremia without acute findings on neuroimaging. Levothyroxine therapy led to complete remission of neuropsychiatric symptoms, and pembrolizumab was safely restarted with close monitoring and no recurrence. This case underscores the importance of assessing thyroid function in acute psychiatric presentations during immune checkpoint inhibitor therapy and supports cautious rechallenge after stabilization. Severe hypothyroidism was considered a major contributor, although a multifactorial delirium, including the contribution of hyponatremia and the absence of CSF/EEG evaluation, cannot be excluded.

Background/Objectives: Access to specialists and diagnostic resources continues to limit differential diagnosis of cognitive impairment in primary care. This pilot study examined the feasibility, usability, and clinical integration of a digitally supported Remote Cognitive Assessment (RCA) model embedded in general practice settings. Methods: A mixed-method design was used, combining structured quantitative surveys from patients (n = 10; mean age = 77.03; SD = 14.1) and neuropsychologists (10 RCAs completed by three neuropsychologists) with qualitative interviews from general practitioners (GP; n = 4). Patients were assessed remotely via a secure videoconference system operated by trained neuropsychologists. Assessments were conducted in the GP’s office, supported by local staff, to facilitate the process. Results: Patients reported high satisfaction with audio (M = 8; SD = 2.28) and video quality (M = 9.17; SD = 1.17) and expressed a strong willingness to recommend RCA (M = 8.83; SD = 1.17) on a 10-point Likert scale. Despite moderate scores for perceived simplicity (M = 5; SD = 3.41) and effectiveness (M = 5.83; SD = 2.14), overall acceptance (M = 8.33; SD = 0.82) was favorable, especially given the older age of participants. Neuropsychologists rated technical functionality positively (audio quality M = 8.17; SD = 1.18; video quality M = 8; SD = 1.67) but raised concerns about clinical utility and diagnostic depth (effectiveness M = 2.83; SD = 2.71). GPs highlighted the benefits of local facilitation, early screening, and improved access to specialist input while also noting space limitations, communication gaps, and the need for sustainable infrastructure. Conclusions: The RCA model was well accepted by patients and GPs, and technically feasible for neuropsychologists. However, neuropsychologists reported important reservations regarding usability and effectiveness. The results suggest an important mismatch between patient satisfaction and clinical confidence and RCA cannot yet be recommended for routine clinical implementations based on patient acceptability alone. This model holds promises for hybrid cognitive care, particularly in underserved or rural areas, but future development must prioritize diagnostic confidence and clinician workflow usability before scalable integration into rural cognitive care pathways can be established.