Background and Purpose— Visual neglect is a frequent disability in stroke and adversely affects mobility, discharge destination, and length of hospital stay. It is assumed that its severity is enhanced by a released interhemispheric inhibition from the unaffected toward the affected hemisphere. Continuous theta burst transcranial magnetic stimulation (TBS) is a new inhibitory brain stimulation protocol which has the potential to induce behavioral effects outlasting stimulation. We aimed to test whether parietal TBS over the unaffected hemisphere can induce a long-lasting improvement of visual neglect by reducing the interhemispheric inhibition. Methods— Eleven patients with left-sided visual neglect attributable to right hemispheric stroke were tested in a visual perception task. To evaluate the specificity of the TBS effect, 3 conditions were tested: 2 TBS trains over the left contralesional posterior parietal cortex, 2 trains of sham stimulation over the contralesional posterior parietal cortex, and a control condition without any intervention. To evaluate the lifetime of repeated trains of TBS in 1 session, 4 trains were applied over the contralesional posterior parietal cortex. Results— Two TBS trains significantly increased the number of perceived left visual targets for up to 8 hours as compared to baseline. No significant improvement was found with sham stimulation or in the control condition without any intervention. The application of 4 TBS trains significantly increased the number of perceived left targets up to 32 hours. Conclusions— The new approach of repeating TBS at the same day may be promising for therapy of neglect.

Left-sided spatial neglect is a common neurological syndrome following right-hemispheric stroke. The presence of spatial neglect is a powerful predictor of poor rehabilitation outcome. In one influential account of spatial neglect, interhemispheric inhibition is impaired and leads to a pathological hyperactivity in the contralesional hemisphere, resulting in a biased attentional allocation towards the right hemifield. Inhibitory transcranial magnetic stimulation can reduce the hyperactivity of the contralesional, intact hemisphere and thereby improve spatial neglect symptoms. However, it is not known whether this improvement is also relevant to the activities of daily living during spontaneous behaviour. The primary aim of the present study was to investigate whether the repeated application of continuous theta burst stimulation trains could ameliorate spatial neglect on a quantitative measure of the activities of daily living during spontaneous behaviour. We applied the Catherine Bergego Scale, a standardized observation questionnaire that can validly and reliably detect the presence and severity of spatial neglect during the activities of daily living. Eight trains of continuous theta burst stimulation were applied over two consecutive days on the contralesional, left posterior parietal cortex in patients suffering from subacute left spatial neglect, in a randomized, double-blind, sham-controlled design, which also included a control group of neglect patients without stimulation. The results showed a 37% improvement in the spontaneous everyday behaviour of the neglect patients after the repeated application of continuous theta burst stimulation. Remarkably, the improvement persisted for at least 3 weeks after stimulation. The amelioration of spatial neglect symptoms in the activities of daily living was also generally accompanied by significantly better performance in the neuropsychological tests. No significant amelioration in symptoms was observed after sham stimulation or in the control group without stimulation. These results provide Class I evidence that continuous theta burst stimulation is a viable add-on therapy in neglect rehabilitation that facilitates recovery of normal everyday behaviour.

Crossing a street can be a very difficult task for older pedestrians. With increased age and potential cognitive decline, older people take the decision to cross a street primarily based on vehicles’ distance, and not on their speed. Furthermore, older pedestrians tend to overestimate their own walking speed, and could not adapt it according to the traffic conditions. Pedestrians’ behavior is often tested using virtual reality. Virtual reality presents the advantage of being safe, cost-effective, and allows using standardized test conditions. This paper describes an observational study with older and younger adults. Street crossing behavior was investigated in 18 healthy, younger and 18 older subjects by using a virtual reality setting. The aim of the study was to measure behavioral data (such as eye and head movements) and to assess how the two age groups differ in terms of number of safe street crossings, virtual crashes, and missed street crossing opportunities. Street crossing behavior, eye and head movements, in older and younger subjects, were compared with non-parametric tests. The results showed that younger pedestrians behaved in a more secure manner while crossing a street, as compared to older people. The eye and head movements analysis revealed that older people looked more at the ground and less at the other side of the street to cross. The less secure behavior in street crossing found in older pedestrians could be explained by their reduced cognitive and visual abilities, which, in turn, resulted in difficulties in the decision-making process, especially under time pressure. Decisions to cross a street are based on the distance of the oncoming cars, rather than their speed, for both groups. Older pedestrians look more at their feet, probably because of their need of more time to plan precise stepping movement and, in turn, pay less attention to the traffic. This might help to set up guidelines for improving senior pedestrians’ safety, in terms of speed limits, road design, and mixed physical-cognitive trainings.

Spatial neglect is a strong and negative predictor of general functional outcome after stroke, and its therapy remains a challenge. Whereas inhibitory non-invasive brain stimulation over the contralesional, intact hemisphere has generally been shown to ameliorate neglect on a group level, a conspicuous variability of the effects at the individual level is typically observed. We aimed to assess the characteristics and determinants of the effects of inhibitory non-invasive brain stimulation in neglect, identifying which patients would respond to this therapeutic approach and which not. To this end, we prospectively included 60 patients with a subacute right-hemispheric stroke. In 30 patients with spatial neglect, continuous theta burst stimulation (cTBS) was applied over the left posterior parietal cortex in a randomized clinical trial, either in eight or 16 trains, or as sham stimulation. Thirty patients without neglect served as a control group. Neglect severity was measured with a neuropsychological test battery and the Catherine Bergego Scale, at admission to and at discharge from inpatient neurorehabilitation, as well as at 3 months follow-up. General functional outcome was assessed by means of the Functional Independence Measure and the Lucerne ICF-based Multidisciplinary Observation Scale. The impact of clinical and demographic factors was evaluated, and the influence of lesion location and extension was assessed by means of voxel-based lesion-symptom mapping. On a group level, both cTBS protocols (i.e. eight and 16 trains) significantly reduced neglect severity in both the Catherine Bergego Scale and the neuropsychological tests, at discharge and 3 months later. Furthermore, cTBS significantly improved general functional outcome. On an individual level, hierarchical cluster and voxel-based lesion-symptom mapping analyses revealed that the variability in the responses to cTBS is determined by the integrity of interhemispheric connections within the corpus callosum, in particular parieto-parietal connections. In cTBS responders, in whom neglect and general functional outcome were significantly improved, the corpus callosum was intact, whereas this was not the case in cTBS non-responders. Moreover, analyses based on the proportional recovery rule and the Maugeri predictive stroke recovery model showed that the recovery of neglect and of the activities of daily living was accelerated only in cTBS responders. Furthermore, the level of activities of daily living recovery of these neglect patients was brought close to the one of right-hemispheric control patients without neglect. Hence, in neglect patients with intact interhemispheric connectivity, cTBS over the contralesional posterior parietal cortex significantly improves and accelerates neglect recovery and, associated with it, general functional outcome.

Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.