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.

Comparison of pain-resilient working individuals to population-based case controls with/without momentary low back pain

Background: Few studies have examined the 20% of individuals who never experience an episode of low back pain (LBP). To date, no investigation has been undertaken that examines a group who claim to have never experienced LBP in their lifetime in comparison to two population-based case–control groups with and without momentary LBP. This study investigates whether LBP-resilient workers between 50 and 65 years had better general health, demonstrated more positive health behaviour and were better able to achieve routine activities compared with both case–control groups. Methods: Forty-two LBP-resilient participants completed the same pain assessment questionnaire as a population-based LBP sample from a nationwide, large-scale cross-sectional survey in Switzerland. The LBP-resilient participants were pairwise compared to the propensity score-matched case controls by exploring differences in demographic and work characteristics, and by calculating odds ratios (ORs) and effect sizes. A discriminant analysis explored group differences, while the multiple logistic regression analysis specified single indicators which accounted for group differences. Results: LBP-resilient participants were healthier than the case controls with momentary LBP and achieved routine activities more easily. Compared to controls without momentary LBP, LBP-resilient participants had a higher vitality, a lower workload, a healthier attitude towards health and behaved more healthily by drinking less alcohol. Conclusions: By demonstrating a difference between LBP-resilient participants and controls without momentary LBP, the question that arises is what additional knowledge can be attained. Three underlying traits seem to be relevant about LBP-resilient participants: personality, favourable work conditions and subjective attitudes/attributions towards health. These rationales have to be considered with respect to LBP prevention.

Effects of task modality, length and complexity on time for activities in lucid dreams

Introduction: Nocturnal dreams can be considered as a kind of simulation of the real world on a higher cognitive level (Erlacher & Schredl, 2008). Within lucid dreams, the dreamer is aware of the dream state and thus able to control the ongoing dream content. Previous studies could demonstrate that it is possible to practice motor tasks during lucid dreams and doing so improved performance while awake (Erlacher & Schredl, 2010). Even though lucid dream practice might be a promising kind of cognitive rehearsal in sports, little is known about the characteristics of actions in lucid dreams. The purpose of the present study was to explore the relationship between time in dreams and wakefulness because in an earlier study (Erlacher & Schredl, 2004) we found that performing squads took lucid dreamers 44.5 % more time than in the waking state while for counting the same participants showed no differences between dreaming and wakefulness. To find out if the task modality, the task length or the task complexity require longer times in lucid dreams than in wakefulness three experiments were conducted. Methods: In the first experiment five proficient lucid dreamers spent two to three non-consecutive nights in the sleep laboratory with polysomnographic recording to control for REM sleep and determine eye signals. Participants counted from 1-10, 1-20 and 1-30 in wakefulness and in their lucid dreams. While dreaming they marked onset of lucidity as well as beginning and end of the counting task with a Left-Right-Left-Right eye movement and reported their dreams after being awakened. The same procedure was used for the second experiment with seven lucid dreamers except that they had to walk 10, 20 or 30 steps. In the third experiment nine participants performed an exercise involving gymnastics elements such as various jumps and a roll. To control for length of the task the gymnastic exercise in the waking state lasted about the same time as walking 10 steps. Results: As a general result we found – as in the study before – that performing a task in the lucid dream requires more time than in wakefulness. This tendency was found for all three tasks. However, there was no difference for the task modality (counting vs. motor task). Also the relative time for the different lengths of the tasks showed no difference. And finally, the more complex motor task (gymnastic routine) did not require more time in lucid dreams than the simple motor task. Discussion/Conclusion: The results showed that there is a robust effect of time in lucid dreams compared to wakefulness. The three experiments could not explain that those differences are caused by task modality, task length or task complexity. Therefore further possible candidates needs to be investigated e.g. experience in lucid dreaming or psychological variables. References: Erlacher, D. & Schredl, M. (2010). Practicing a motor task in a lucid dream enhances subsequent performance: A pilot study. The Sport Psychologist, 24(2), 157-167. Erlacher, D. & Schredl, M. (2008). Do REM (lucid) dreamed and executed actions share the same neural substrate? International Journal of Dream Research, 1(1), 7-13. Erlacher, D. & Schredl, M. (2004). Time required for motor activity in lucid dreams. Perceptual and Motor Skills, 99, 1239-1242.