Eye examining instrument

An eye examining instrument comprises a projection device and a concave screen. The eye examining instrument furthermore comprises a convex reflector, wherein an image can be projected by the projection device onto the convex reflector and reflected by the convex reflector onto the concave screen.

Distribution of human immunodeficiency virus (HIV) in the CNS of children with severe HIV encephalomyelopathy

The presence and distribution of human immunodeficiency virus (HIV) were examined in the CNS of two children with severe HIV encephalitis and myelitis. Using polymerase chain reaction-mediated DNA amplification and subsequent Southern analysis, proviral HIV gag sequences were identified in brain tissue of both patients. In situ hybridization using antisense oligonucleotide probes revealed abundant HIV gag and env/nef RNAs selectively in areas with histopathological evidence for HIV-induced tissue damage. The spinal cord of one patient exhibited a striking subpial accumulation of HIV RNAs strongly suggestive of a liquorigenic spread of the infection. HIV RNAs were typically associated with cells of the monocyte/macrophage lineage, as shown by a combined immunohistochemical and in situ hybridization procedure. The present study supports the view that the pattern and distribution of HIV-induced brain lesions is largely determined by the extent of focal HIV replication within the CNS.

Cardiopulmonary performance testing using a robotics-assisted tilt table: Feasibility assessment in able-bodied subjects

BACKGROUND: Robotics-assisted tilt table technology was introduced for early rehabilitation of neurological patients. It provides cyclical stepping movement and physiological loading of the legs. The aim of the present study was to assess the feasibility of this type of device for peak cardiopulmonary performance testing using able-bodied subjects. METHODS: A robotics-assisted tilt table was augmented with force sensors in the thigh cuffs and a work rate estimation algorithm. A custom visual feedback system was employed to guide the subjects' work rate and to provide real time feedback of actual work rate. Feasibility assessment focused on: (i) implementation (technical feasibility), and (ii) responsiveness (was there a measurable, high-level cardiopulmonary reaction?). For responsiveness testing, each subject carried out an incremental exercise test to the limit of functional capacity with a work rate increment of 5 W/min in female subjects and 8 W/min in males. RESULTS: 11 able-bodied subjects were included (9 male, 2 female; age 29.6 ± 7.1 years: mean ± SD). Resting oxygen uptake (O_{2}) was 4.6 ± 0.7 mL/min/kg and O_{2}peak was 32.4 ± 5.1 mL/min/kg; this mean O_{2}peak was 81.1% of the predicted peak value for cycle ergometry. Peak heart rate (HRpeak) was 177.5 ± 9.7 beats/min; all subjects reached at least 85% of their predicted HRpeak value. Respiratory exchange ratio (RER) at O_{2}peak was 1.02 ± 0.07. Peak work rate) was 61.3 ± 15.1 W. All subjects reported a Borg CR10 value for exertion and leg fatigue of 7 or more. CONCLUSIONS: The robotics-assisted tilt table is deemed feasible for peak cardiopulmonary performance testing: the approach was found to be technically implementable and substantial cardiopulmonary responses were observed. Further testing in neurologically-impaired subjects is warranted.

Manipulations to reduce simulator-related transient adverse health effects during simulated driving

User comfort during simulated driving is of key importance, since reduced comfort can confound the experiment and increase dropout rates. A common comfort-affecting factor is simulator-related transient adverse health effect (SHE). In this study, we propose and evaluate methods to adapt a virtual driving scene to reduce SHEs. In contrast to the manufacturer-provided high-sensory conflict scene (high-SCS), we developed a low-sensory conflict scene (low-SCS). Twenty young, healthy participants drove in both the high-SCS and the low-SCS scene for 10 min on two different days (same time of day, randomized order). Before and after driving, participants rated SHEs by completing the Simulator Sickness Questionnaire (SSQ). During driving, several physiological parameters were recorded. After driving in the high-SCS, the SSQ score increased in average by 129.4 (122.9 %, p = 0.002) compared to an increase of 5.0 (3.4 %, p = 0.878) after driving in the low-SCS. In the low-SCS, skin conductance decreased by 13.8 % (p < 0.01) and saccade amplitudes increased by 16.1 % (p < 0.01). Results show that the investigated methods reduce SHEs in a younger population, and the low-SCS is well accepted by the users. We expect that these measures will improve user comfort.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

A new method to measure higher visual functions in an immersive environment

BACKGROUND: Higher visual functions can be defined as cognitive processes responsible for object recognition, color and shape perception, and motion detection. People with impaired higher visual functions after unilateral brain lesion are often tested with paper pencil tests, but such tests do not assess the degree of interaction between the healthy brain hemisphere and the impaired one. Hence, visual functions are not tested separately in the contralesional and ipsilesional visual hemifields. METHODS: A new measurement setup, that involves real-time comparisons of shape and size of objects, orientation of lines, speed and direction of moving patterns, in the right or left visual hemifield, has been developed. The setup was implemented in an immersive environment like a hemisphere to take into account the effects of peripheral and central vision, and eventual visual field losses. Due to the non-flat screen of the hemisphere, a distortion algorithm was needed to adapt the projected images to the surface. Several approaches were studied and, based on a comparison between projected images and original ones, the best one was used for the implementation of the test. Fifty-seven healthy volunteers were then tested in a pilot study. A Satisfaction Questionnaire was used to assess the usability of the new measurement setup. RESULTS: The results of the distortion algorithm showed a structural similarity between the warped images and the original ones higher than 97%. The results of the pilot study showed an accuracy in comparing images in the two visual hemifields of 0.18 visual degrees and 0.19 visual degrees for size and shape discrimination, respectively, 2.56° for line orientation, 0.33 visual degrees/s for speed perception and 7.41° for recognition of motion direction. The outcome of the Satisfaction Questionnaire showed a high acceptance of the battery by the participants. CONCLUSIONS: A new method to measure higher visual functions in an immersive environment was presented. The study focused on the usability of the developed battery rather than the performance at the visual tasks. A battery of five subtasks to study the perception of size, shape, orientation, speed and motion direction was developed. The test setup is now ready to be tested in neurological patients.

Enhancing treatment effects by combining continuous theta burst stimulation with smooth pursuit training

Continuous theta burst stimulation (cTBS) represents a promising approach in the treatment of neglect syndrom. However, it is not known whether cTBS in conjunction with another technique may enhance the therapeutic effects. In the present sham-controlled study, we aimed to combine cTBS with smooth pursuit training (SPT), another method known to effectively improve neglect symptoms, and to evaluate whether this combination would result in a stronger effect than SPT alone. Eighteen patients with left spatial neglect after right-hemispheric stroke were included in the study and performed a cancellation task on a large 54.6" touchscreen monitor. A sequential application of cTBS and SPT induced a significantly greater improvement of neglect than SPT alone. After the combined application of these two methods, patients detected significantly more targets and their cancellation behaviour presented a significantly greater shift towards the contralesional hemispace. We suggest that a combined, sequential application of cTBS and SPT is a promising new approach to treat neglect.

Patient and Informant Views on Visual Hallucinations in Parkinson Disease.

OBJECTIVE Visual hallucinations (VHs) are a very personal experience, and it is not clear whether information about them is best provided by informants or patients. Some patients may not share their hallucinatory experiences with caregivers to avoid distress or for fear of being labeled insane, and others do not have informants at all, which limits the use of informant-based questionnaires. The aim of this study was to compare patient and caregiver views about VHs in Parkinson disease (PD), using the North-East Visual Hallucinations Interview (NEVHI). METHODS Fifty-nine PD patient-informant pairs were included. PD patients and informants were interviewed separately about VHs using the NEVHI. Informants were additionally interviewed using the four-item version of the Neuropsychiatric Inventory. Inter-reliability and concurrent validity of the different measures were compared. RESULTS VHs were more commonly reported by patients than informants. The inter-rater agreement between NEVHI-patient and NEVHI-informant was moderate for complex VHs (Cohen's kappa = 0.44; 95% confidence interval [CI]: 0.13-0.75; t = 3.43, df = 58, p = 0.001) and feeling of presence (Cohen's kappa = 0.35; 95% CI: 0.00-0.70; t = 2.75, df = 58, p = 0.006), but agreement was poor for illusions (Cohen's kappa = 0.25; 95% CI: -0.07-0.57; t = 2.36, df = 58, p = 0.018) and passage hallucinations (Cohen's kappa = 0.16; 95% CI: -0.04-0.36; t = 2.26, df = 58, p = 0.024). CONCLUSION When assessing VHs in PD patients, it is best to rely on patient information, because not all patients share the details of their hallucinations with their caregivers.

On the comparison of a novel serious game and electroencephalography biomarkers for early dementia screening

Patients with amnestic mild cognitive impairment are at high risk for developing Alzheimer's disease. Besides episodic memory dysfunction they show deficits in accessing contextual knowledge that further specifies a general spatial navigation task or an executive function (EF) virtual action planning. Virtual reality (VR) environments have already been successfully used in cognitive rehabilitation and show increased potential for use in neuropsychological evaluation allowing for greater ecological validity while being more engaging and user friendly. In our study we employed the in-house platform of virtual action planning museum (VAP-M) and a sample of 25 MCI and 25 controls, in order to investigate deficits in spatial navigation, prospective memory, and executive function. In addition, we used the morphology of late components in event-related potential (ERP) responses, as a marker for cognitive dysfunction. The related measurements were fed to a common classification scheme facilitating the direct comparison of both approaches. Our results indicate that both the VAP-M and ERP averages were able to differentiate between healthy elders and patients with amnestic mild cognitive impairment and agree with the findings of the virtual action planning supermarket (VAP-S). The sensitivity (specificity) was 100% (98%) for the VAP-M data and 87% (90%) for the ERP responses. Considering that ERPs have proven to advance the early detection and diagnosis of "presymptomatic AD," the suggested VAP-M platform appears as an appealing alternative.

Effect of Cognitive Impairment on Driving-Relevant Cognition in Older Persons

Intact cognitive abilities are fundamental for driving. Driving-relevant cognition may be affected in older drivers due to aging or cognitive impairment. The aim of this study was to investigate the effects of cognitive impairment on driving-relevant cognition in older persons. Performance in selective and divided attention, eye-hand-coordination, executive functions and the ability to regulate distance and speed of 18 older persons with CI-Group (cognitive impairment group) was compared to performance of older control group (18 age and gender-matched cognitively normal subjects) and young control group (18 gender-matched young subjects). The CI-Group showed poorer performance than the other two control groups in all cognitive tasks (significance level (p) < 0.001, effect size (partial η2) = 0.63). Differences between cognitively impaired and cognitively normal subjects were still significant after controlling for age (effect sizes from 0.14 to 0.28). Dual tasking affected performance of cognitively impaired subjects more than performance of the other two groups (p = 0.016, partial η2 = 0.14). Results show that cognitive impairment has age-independent detrimental effects on selective and divided attention, eye-hand-coordination, executive functions and the ability to regulate distance and speed. Largest effect sizes are found for reaction times in attention tasks.

The role of the right frontal eye field in overt visual attention deployment as assessed by free visual exploration

The frontal eye field (FEF) is known to be involved in saccade generation and visual attention control. Studies applying covert attentional orienting paradigms have shown that the right FEF is involved in attentional shifts to both the left and the right hemifield. In the current study, we aimed at examining the effects of inhibitory continuous theta burst (cTBS) transcranial magnetic stimulation over the right FEF on overt attentional orienting, as measured by a free visual exploration paradigm. In forty-two healthy subjects, free visual exploration of naturalistic pictures was tested in three conditions: (1) after cTBS over the right FEF; (2) after cTBS over a control site (vertex); and, (3) without any stimulation. The results showed that cTBS over the right FEF-but not cTBS over the vertex-triggered significant changes in the spatial distribution of the cumulative fixation duration. Compared to the group without stimulation and the group with cTBS over the vertex, cTBS over the right FEF decreased cumulative fixation duration in the left and in the right peripheral regions, and increased cumulative fixation duration in the central region. The present study supports the view that the right FEF is involved in the bilateral control of not only covert, but also of overt, peripheral visual attention.

Development of a novel driving behavior adaptations questionnaire

ABSTRACT Background: Driving a car requires adapting one's behavior to current task demands taking into account one's capacities. With increasing age, driving-relevant cognitive performance may decrease, creating a need for risk-reducing behavioral adaptations. Three different kinds of behavioral adaptations are known: selection, optimization, and compensation. These can occur on the tactical and the strategic level. Risk-reducing behavioral adaptations should be considered when evaluating older drivers' traffic-related risks. Methods: A questionnaire to assess driving-related behavioral adaptations in older drivers was created. The questionnaire was administered to 61 years older (age 65-87 years; mean age = 70.2 years; SD = 5.5 years; 30 female, 31 male) and 31 younger participants (age 22-55 years; mean age = 30.5 years; SD = 6.3 years; 16 female and 15 male) to explore age and gender differences in behavioral adaptations. Results: Two factors were extracted from the questionnaire, a risk-increasing factor and a risk-reducing factor. Group comparisons revealed significantly more risk-reducing behaviors in older participants (t(84.5) = 2.21, p = 0.013) and females (t(90) = 2.52, p = 0.014) compared, respectively, to younger participants and males. No differences for the risk-increasing factor were found (p > 0.05). Conclusions: The questionnaire seems to be a useful tool to assess driving-related behavioral adaptations aimed at decreasing the risk while driving. The possibility to assess driving-related behavioral adaptations in a systematic way enables a more resource-oriented approach in the evaluation of fitness to drive in older drivers.

Neglect and Motion Stimuli - Insights from a Touchscreen-Based Cancellation Task

BACKGROUND AND PURPOSE: In stroke patients, neglect diagnostic is often performed by means of paper-pencil cancellation tasks. These tasks entail static stimuli, and provide no information concerning possible changes in the severity of neglect symptoms when patients are confronted with motion. We therefore aimed to directly contrast the cancellation behaviour of neglect patients under static and dynamic conditions. Since visual field deficits often occur in neglect patients, we analysed whether the integrity of the optic radiation would influence cancellation behaviour. METHODS: Twenty-five patients with left spatial neglect after right-hemispheric stroke were tested with a touchscreen cancellation task, once when the evenly distributed targets were stationary, and once when the identic targets moved with constant speed on a random path. The integrity of the right optic radiation was analysed by means of a hodologic probabilistic approach. RESULTS: Motion influenced the cancellation behaviour of neglect patients, and the direction of this influence (i.e., an increase or decrease of neglect severity) was modulated by the integrity of the right optic radiation. In patients with an intact optic radiation, the severity of neglect significantly decreased in the dynamic condition. Conversely, in patients with damage to the optic radiation, the severity of neglect significantly increased in the dynamic condition. CONCLUSION: Motion may influence neglect in stroke patients. The integrity of the optic radiation may be a predictor of whether motion increases or decreases the severity of neglect symptoms.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

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.