Real-world fall events objectively measured by body-worn sensors can improve the understanding of fall events in older people. However, these events are rare and hence challenging to capture. Therefore, the FARSEEING (FAll Repository for the design of Smart and sElf-adaptive Environments prolonging Independent livinG) consortium and associated partners started to build up a meta-database of real-world falls. Between January 2012 and December 2015 more than 300 real-world fall events have been recorded. This is currently the largest collection of real-world fall data recorded with inertial sensors. A signal processing and fall verification procedure has been developed and applied to the data. Since the end of 2015, 208 verified real-world fall events are available for analyses. The fall events have been recorded within several studies, with different methods, and in different populations. All sensor signals include at least accelerometer measurements and 58 % additionally include gyroscope and magnetometer measurements. The collection of data is ongoing and open to further partners contributing with fall signals. The FARSEEING consortium also aims to share the collected real-world falls data with other researchers on request. The FARSEEING meta-database will help to improve the understanding of falls and enable new approaches in fall risk assessment, fall prevention, and fall detection in both aging and disease.

Falls frequency increases with age and particularly in neurogeriatric cohorts. The interplay between eye movements and locomotion may contribute substantially to the occurrence of falls, but is hardly investigated. This paper provides an overview of current approaches to simultaneously measure eye and body movements, particularly for analyzing the association of vestibulo-ocular reflex (VOR) suppression, postural deficits and falls in neurogeriatric risk cohorts. Moreover, VOR suppression is measured during head-fixed target presentation and during gaze shifting while postural control is challenged. Using these approaches, we aim at identifying quantitative parameters of eye-head-coordination during postural balance and gait, as indicators of fall risk. Patients with Progressive Supranuclear Palsy (PSP) or Parkinson’s disease (PD), age- and sex-matched healthy older adults, and a cohort of young healthy adults will be recruited. Baseline assessment will include a detailed clinical assessment, covering medical history, neurological examination, disease specific clinical rating scales, falls-related self-efficacy, activities of daily living, neuro-psychological screening, assessment of mobility function and a questionnaire for retrospective falls. Moreover, participants will simultaneously perform eye and head movements (fixating a head-fixed target vs. shifting gaze to light emitting diodes in order to quantify vestibulo-ocular reflex suppression ability) under different conditions (sitting, standing, or walking). An eye/head tracker synchronized with a 3-D motion analysis system will be used to quantify parameters related to eye-head-coordination, postural balance, and gait. Established outcome parameters related to VOR suppression ability (e.g., gain, saccadic reaction time, frequency of saccades) and motor related fall risk (e.g., step-time variability, postural sway) will be calculated. Falls will be assessed prospectively over 12 months via protocols and monthly telephone interviews. This study protocol describes an experimental setup allowing the analysis of simultaneously assessed eye, head and body movements. Results will improve our understanding of the influence of the interplay between eye, head and body movements on falls in geriatric high-risk cohorts.

The incidence of proximal humeral fractures increases with age. The functional recovery of the upper arm after such fractures is slow, and results are often disappointing. Treatment is associated with long immobilisation periods. Evidence-based exercise guidelines are missing. Loss of muscle mass as well as reduced range of motion and motor performance are common consequences. These losses could be partly counteracted by training interventions using robot-assisted arm support of the affected arm derived from neurorehabilitation. Thus, shorter immobilisation could be reached. Thus far, this approach has been tested in only a few small studies. The aim of the present study is to examine whether assistive robotic training augmenting conventional occupational and physical therapy can improve functional shoulder outcomes. Patients aged between 35 and 66 years with proximal humeral fracture and surgical treatment will be recruited at three different clinics in Germany and randomised into an intervention group and a control group. Participants will be assessed before randomisation and followed after completing an intervention period of 3 weeks and additionally after 3, 6 and 12 months. The baseline assessment will include cognition (Short Orientation-Memory-Concentration Test); level of pain in the affected arm; ability to work; gait speed (10-m walk); disability of the arm, shoulder and hand (Disabilities of the Arm, Shoulder and Hand Outcome Measure [DASH]); range of motion of the affected arm (goniometer measurement); visual acuity; and motor function of orthopaedic patients (Wolf Motor Function Test–Orthopaedic version [WMFT-O]). Clinical follow-up directly after the intervention will include assessment of disability of the arm, shoulder and hand (DASH) as well as range of motion and motor function (WMFT-O). The primary outcome parameter will be the DASH, and the secondary outcome parameter will be the WMFT-O. The long-term results will be assessed prospectively by postal follow-up. All patients will receive conventional occupational and physical therapy. The intervention group will receive additional robot-assisted training using the Armeo®Spring robot for 3 weeks. This study protocol describes a phase II, randomised, controlled, single-blind, multicentre intervention study. The results will guide and possibly improve methods of rehabilitation after proximal humeral fracture. Clinicaltrials.gov, NCT03100201 . Registered on 28 March 2017.

This prospective study investigated feasibility and sensitivity of sensor-based physical activity (PA) measures to monitor changes in PA during geriatric rehabilitation and its relation to clinical parameters at admission. PA was routinely measured at day 2 and day 15 after admission in 647 patients (70.2% women, mean age = 82.0 (SD = 7.19) years) of a German geriatric hospital using a thigh-worn accelerometer. Clinical records were used to include age, Barthel Index, diagnosis, mobility, orientation and cognition. Mean values and 95% confidence intervals (95%-CI) of walking duration, walking bout duration and number of sit-to-stand transfers were calculated to quantify different domains of PA. All observed PA parameters improved during rehabilitation, regardless of age, diagnosis or physical and cognitive function at admission. Walking duration increased by 12.1 (95%-CI: 10.3; 13.8) min, walking bout duration by 2.39 (95%-CI: 1.77; 3.00) s, and number of sit-to-stand transfers by 7 (95%-CI: 5; 8). Floor and ceiling effects were not observed. Walking duration at day 2 as well as day 15 was continuously associated with Barthel Index and statistically significant improved for all levels of Barthel Index. In summary, this study showed that sensor-based PA monitoring is feasible to assess the individual progress in geriatric rehabilitation patients.