Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987

Evaluation of the cholinergic hypothesis in Alzheimer's disease with neuropsychological methods

This study aimed at evaluating the cholinergic hypothesis in Alzheimer's disease (AD) patients utilizing the pupillometry method, cognitive tests and Hamilton Depression Rating Scale (HAM-D), as well as to examine whether a correlation between cognitive tests and pupillometry exists. Forty-two patients with mean age 69.2 +/- A 7.0 years and documented AD volunteered to participate in this study, while 33 healthy matched subjects served as controls. All subjects underwent a pupillometric measurement and performed the Wechsler Memory Scale (WMS) and Mini Mental State Examination (MMSE). Also, HAM-D was used to assess the severity of depressive symptoms. The pupillometric parameters studied were (1) latency for the onset of constriction (T1), (2) maximum constriction velocity (VCmax), and (3) maximum constriction acceleration (ACmax). In AD patients MMSE and WMS score were correlated with ACmax (r = -0.409, p < 0.05 and r = -0.513, p < 0.05, respectively) and VCmax (r = -0.664, p < 0.05 and r = -0.771, p < 0.05), respectively. Moreover, T1 was found to be significantly increased by 23 % (p < 0.05) in AD patients compared to healthy subjects. Conversely, the mean scores of VCmax and ACmax were significantly decreased in AD patients by 46 % (p < 0.05) and by 47 % (p < 0.05), respectively, as compared to healthy subjects. There was no significant difference between the two groups for HAM-D. Additionally, AD patients showed decreased score in WMS by 40 % (p < 0.05) and in MMSE by 28.5 % (p < 0.05) compared to healthy subjects. Of the indices that were studied VCmax and ACmax are governed mainly by the action of the Parasympathetic Nervous System. The results of this study demonstrated that there is a correlation between cognitive tests and pupillometry in AD patients. Thus, pupillometry could be considered as a sensitive technique for the investigation of cholinergic deficits, which indirectly lead to memory and cognitive disorders in AD patients