7 research outputs found

    On the importance of local dynamics in statokinesigram: A multivariate approach for postural control evaluation in elderly

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    <div><p>The fact that almost one third of population >65 years-old has at least one fall per year, makes the risk-of-fall assessment through easy-to-use measurements an important issue in current clinical practice. A common way to evaluate posture is through the recording of the center-of-pressure (CoP) displacement (statokinesigram) with force platforms. Most of the previous studies, assuming homogeneous statokinesigrams in quiet standing, used global parameters in order to characterize the statokinesigrams. However the latter analysis provides little information about local characteristics of statokinesigrams. In this study, we propose a multidimensional scoring approach which locally characterizes statokinesigrams on small time-periods, or <i>blocks</i>, while highlighting those which are more indicative to the general individual’s class (faller/non-faller). Moreover, this information can be used to provide a global score in order to evaluate the postural control and classify fallers/non-fallers. We evaluate our approach using the statokinesigram of 126 community-dwelling elderly (78.5 ± 7.7 years). Participants were recorded with eyes open and eyes closed (25 seconds each acquisition) and information about previous falls was collected. The performance of our findings are assessed using the receiver operating characteristics (ROC) analysis and the area under the curve (AUC). The results show that global scores provided by splitting statokinesigrams in smaller blocks and analyzing them locally, classify fallers/non-fallers more effectively (AUC = 0.77 ± 0.09 instead of AUC = 0.63 ± 0.12 for global analysis when splitting is not used). These promising results indicate that such methodology might provide supplementary information about the risk of fall of an individual and be of major usefulness in assessment of balance-related diseases such as Parkinson’s disease.</p></div

    Demographic characteristics of the participants.

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    <p>Fallers are patient who declared at least one fall in the six previous months. No statistically significant difference was found between the two population regarding age, weight, height and body mass index (BMI).</p

    Probability density for the two-component mixture distribution (95%) and three-second-blocks of A) Non-fallers and B)Fallers, illustrated in the normalized 3-dimensional space.

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    <p>The two normal components overlap, but their centers are distinct. Many faller-derived periods are closer to the QBs component and conversely, many non-faller derived blocks are closer to the UBs centre.</p

    Classification performance of the global score using different block-lengths.

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    <p>While reasonable lengths performed almost equally, when block separation is not used (processing raw signals as one block), area under the curve (AUC) was significantly lower. * indicates that AUC derived by no block-separation is significantly lower than the others (p<0.001).</p

    Representation of the score of the different blocks for a statokinesigram deduced from the CoP antero-posterior and medio-lateral using multiple block-lengths and 50% overlap.

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    <p>A large value (yellow colour) indicates a high probability of belonging to the UBs cluster, while a small value (blue colour) represents a block with low probability of belonging to UBs cluster—and therefore a large probability to belong to the QB cluster. Detail of the analysis using 1-second block-length is provided (orange box).</p
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