Automatic non-linear analysis of non-invasive writing signals, applied to essential tremor

Ipiña, Karmele López de; Bergareche, Alberto; Riva, Patricia de la; Faundez-Zanuy, Marcos; Calvo, Pilar M.; Roure, Josep; Sesa-Nogueras, Enric

doi:10.1016/j.jal.2015.02.003

Cited by 11 publications

(15 citation statements)

References 17 publications

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“…Written informed consent, fully approved by the local ethics committee at the Donostia University Hospital, was obtained from all participants in this new study. Table 1 summarizes the features of the group with ET with regard to EPT, diagnosis and demography [13,14]. In addition to the standard clinical exploration (Neuropsychological and Electrophysiological Studies), evaluation of ET was carried out by recording the drawing of an Archimedes' spiral.…”

Section: Database Of Individualsmentioning

confidence: 99%

“…For instance, people diagnosed with AD produce softer and simpler strokes, and people with ET are less stable. ET and Parkinson's disease are other examples [13,14,[23][24][25]. For example, in [18], they have reported the proficiency of writers with regard to the length of the in-air trajectories and the pressure of their handwritings [26].…”

Section: Pressure Derived Measures and In-air Analysismentioning

confidence: 99%

“…It is part of a wider study focused on early ET detection. Feature search in this work aims at preclinical evaluation in order to define useful tests for ET diagnosis [5,13,14].…”

Section: Features Extractionmentioning

confidence: 99%

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Selection of Entropy Based Features for Automatic Analysis of Essential Tremor

Ipiña

Solé-Casals

Faundez-Zanuy

et al. 2016

Entropy

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Biomedical systems produce biosignals that arise from interaction mechanisms. In a general form, those mechanisms occur across multiple scales, both spatial and temporal, and contain linear and non-linear information. In this framework, entropy measures are good candidates in order provide useful evidence about disorder in the system, lack of information in time-series and/or irregularity of the signals. The most common movement disorder is essential tremor (ET), which occurs 20 times more than Parkinson's disease. Interestingly, about 50%-70% of the cases of ET have a genetic origin. One of the most used standard tests for clinical diagnosis of ET is Archimedes' spiral drawing. This work focuses on the selection of non-linear biomarkers from such drawings and handwriting, and it is part of a wider cross study on the diagnosis of essential tremor, where our piece of research presents the selection of entropy features for early ET diagnosis. Classic entropy features are compared with features based on permutation entropy. Automatic analysis system settled on several Machine Learning paradigms is performed, while automatic features selection is implemented by means of ANOVA (analysis of variance) test. The obtained results for early detection are promising and appear applicable to real environments.

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Section: Database Of Individualsmentioning

confidence: 99%

Section: Pressure Derived Measures and In-air Analysismentioning

confidence: 99%

See 1 more Smart Citation

Selection of Entropy Based Features for Automatic Analysis of Essential Tremor

Ipiña

Solé-Casals

Faundez-Zanuy

et al. 2016

Entropy

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“…It is the most common movement disorder in adults and may be a symptom of a disease or the consequence of drugs [1,2]. For this movement disorder, Essential tremor (ET) and Parkinson's Disease (PD) are the most common disorder and disease, respectively, and the hands are the most affected site [3][4][5][6]. Tremor can be distinguished between rest and action tremor; action tremor can be further classified into different sub groups, e.g.…”

Section: Tremormentioning

confidence: 99%

“…In the overall population of the USA, approximately 2.2% (7 million individuals) are affected by ET [10]. More than 65% of those suffering from tremor in the upper limb present serious difficulties in performing activities in daily life (ADL) [6,11]. Furthermore, 34% of ET and 48% of PD patients were found to be at least mildly depressed [12].…”

Section: Tremormentioning

confidence: 99%

Design of a lightweight passive orthosis for tremor suppression

Fromme

Camenzind

Riener

et al. 2020

J NeuroEngineering Rehabil

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Background: Tremor is the most common movement disorder with the highest prevalence in the upper limbs. The mechanical suppression of involuntary movements is an alternative and additional treatment to medication or surgery. Here we present a new, soft, lightweight, task asjustable and passive orthosis for tremor suppression. Methods: A new concept of a manual, textile-based, passive orthosis was designed with an integrated, task adjustable, air-filled structure, which can easily be inflated or deflated on-demand for a certain daily activity. The airfilled structure is placed on the dorsal side of the wrist and gets bent and compressed by movements when inflated. In a constant volume air-filled structure, air pressure increases while it is inflating, creating a counterforce to the compression caused by bending. We characterised the air-filled structure stiffness by measuring the reaction torque as a function of the angle of deflection on a test bench. Furthermore, we evaluated the efficacy of the developed passive soft orthosis by analysing the suppression of involuntary movements in the wrist of a tremoraffected patient during different activities of daily living (i.e. by calculating the power spectral densities of acceleration). Results: By putting special emphasis on the comfort and wearability of the orthosis, we achieved a lightweight design (33 g). The measurements of the angular deflection and resulting reaction torques show non-linear, hysteretic, behaviour, as well as linear behaviour with a coefficient of determination (R 2) between 0.95 and 0.99. Furthermore, we demonstrated that the soft orthosis significantly reduces tremor power for daily living activities, such as drinking from a cup, pouring water and drawing a spiral, by 74 to 82% (p = 0.03); confirmed by subjective tremor-reducing perception by the patient. Conclusion: The orthosis we developed is a lightweight and unobtrusive assistive technology, which suppresses involuntary movements and shows high wearability properties, with the potential to be comfortable. This airstructure technology could also be applied to other movement disorders, like spasticity, or even be integrated into future exoskeletons and exosuits for the implementation of variable stiffness in the systems.

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The Effect of Fatigue on the Performance of Online Writer Recognition

Sesa-Nogueras¹,

Faundez-Zanuy²,

Garnacho-Castaño³

2021

Cogn Comput

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Background: The performance of biometric modalities based on things done by the subject, like signature and text-based recognition, may be affected by the subject's state. Fatigue is one of the conditions that can significantly affect the outcome of handwriting tasks. Recent research has already shown that physical fatigue produces measurable differences in some features extracted from common writing and drawing tasks. It is important to establish to which extent physical fatigue contributes to the intra-person variability observed in these biometric modalities and also to know whether the performance of recognition methods is affected by fatigue. Goal: In this paper we assess the impact of fatigue on intra-user variability and on the performance of signature-based and text-based writer recognition approaches encompassing both identification and verification. Methods: Several signature and text recognition methods are considered and applied to samples gathered after different levels of induced fatigue, measured by metabolic and mechanical assessment and, also by subjective perception. The recognition methods are Dynamic Time Warping and Multi Section Vector Quantization, for signatures, and Allographic Text-Dependent Recognition for text in capital letters. For each fatigue level, the identification and verification performance of these methods is measured. Results: Signature shows no statistically significant intra-user impact, but text does. On the other hand, performance of signature-based recognition approaches is negatively impacted by fatigue whereas the impact is not noticeable in text-based recognition, provided long enough sequences are considered.

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Automatic non-linear analysis of non-invasive writing signals, applied to essential tremor

Cited by 11 publications

References 17 publications

Selection of Entropy Based Features for Automatic Analysis of Essential Tremor

Selection of Entropy Based Features for Automatic Analysis of Essential Tremor

Design of a lightweight passive orthosis for tremor suppression

The Effect of Fatigue on the Performance of Online Writer Recognition

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