Regression models for the quantification of Parkinsonian bradykinesia

Kim, Ji Won; Kwon, Yongkyung; Yun, Ju Seok; Heo, Jae-Hyeok; Eom, Gwang-Moon; Tack, Gye−Rae; Lim, Tae-Hong; Koh, Seong Beom

doi:10.3233/bme-151531

Cited by 9 publications

(10 citation statements)

References 13 publications

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“…The gyro sensor has been used to quantitatively analyze the clinical features for patients with movement disorders because it can measure angular movements and is free from gravity artifact. Indeed, many studies have attempted quantitative analysis of bradykinesia by using gyro sensors in PD patients [ 14 , 15 , 16 , 17 ] and scans without evidence of dopaminergic deficit (SWEDD) [ 15 ]. Although Parkinson’s tremor has been investigated by using the gyro sensor [ 23 , 24 ], quantitative measures of ET have still been required because of the difference of clinical features between ET and Parkinson’s tremors.…”

Section: Discussionmentioning

confidence: 99%

“…That is, the gyro sensor was shown to be helpful for the evaluation of tremor patterns. Actually, it has been reported that the gyro sensor based system was used to quantify upper limb bradykinesia [ 14 , 15 , 16 ] as well as lower limb bradykinesia [ 17 ] in patients with Parkinson’s disease (PD). Moreover, quantitative evaluation of motor function in patients with mild-to-moderate carpal tunnel syndrome was investigated using the gyro sensor [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

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Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor

Kwon

Choi

et al. 2020

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BACKGROUND: It is important to quantitatively assess tremor for accurate diagnosis and evaluation of the response to interventions in patients with essential tremor (ET). OBJECTIVE: The purpose of this study was to investigate the relationship between quantitative measures of postural tremor and clinical rating scale in patients with ET. METHODS: 18 ET patients performed a postural tremor task that required them to hold their arms outstretched parallel to the floor while wearing a gyro sensor based measurement system. The time domain variables were derived from the sensor signals. Additionally, the frequency domain variables were derived from the power spectrum of the angular velocity signal. Spearman correlation analysis was employed in the relationship between the variables and clinical score. RESULTS: The RMS angular velocity of roll and yaw directions at the hand joint were strongly correlated with the clinical rating scale (r = 0.7, p < 0.01). Similarly, the peak power of roll and yaw directions at the hand joint were moderately correlated with the clinical rating scale (r = 0.61 and r = 0.67, p < 0.01). In contrast, no significant correlation coefficients were observed in the peak frequency (p > 0.05). CONCLUSION: These results indicate that hand tremor of roll and yaw directions are more associated with assessment of severity of ET compared to other joints. This study suggests that quantitative measurements of postural tremor should be considered as tremor directionality as well as attachment location.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor

Kwon

Choi

et al. 2020

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“…Todos os trabalhos selecioandos avaliam a bradicinesia conforme as ativdidades porpostas pela UPDRS e a maioria destes utilizou os parâmetros derivados da velocidade angular [11]- [14] [15].…”

Section: Discussionunclassified

“…Jun et al [13], a partir da velocidade angular extraíram o valor médio de ângulo, pico de potência e potência total ao executar o movimento de pronação e supinação da mão. Kim et al [14], por meio de um giroscópio, extraíram os parâmetros de ângulo, pico de potência e potência média do movimento de batidas dos dedos.…”

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Uma Revisão Dos Métodos Para Avaliação Da Bradicinesia Parkinsoniana Utilizando Sensores Inerciais

Rabelo¹,

Oliveira²,

Vieira³

et al. 2018

Anais Do v Congresso Brasileiro De Eletromiografia E Cinesiologia E X Simpósio De Engenharia Biomédica

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Resumo: A avaliação da bradicinesia parkinsoniana tem sido foco de vários trabalhos e a maioria desses estudos utiliza escalas subjetivas para a sua avaliação. Recentemente, algumas pesquisas têm proposto a avaliação da bradicinesia por meio de sensores inerciais. Uma das principais dificuldades na realização desses estudos é relacionada à identificação de parâmetros extraídos dos sinais mensurados, que possibilitem a caracterização de padrões de normalidade e bradicinesia. Neste sentido, essa pesquisa traz uma revisão dos trabalhos que avaliam a bradicinesia usando a extração de parâmetros de sinais medidos por sensores inerciais. Embora a presença do tremor seja altamente relacionada a DP, a incidência da bradicinesia em estágios avançados da doença pode ser muito maior [4]. PalavrasA bradicinesia está relacionada não somente com a lentidão ao executar movimentos, mas também com a diminuição e hesitações [5]. É o sinal mais incapacitante para pacientes com DP [6]. Rosano et al. [7] avaliaram desordens motoras na marcha em idosos e constatou que 25% dos participantes da pesquisa possuíam bradicinesia.Há motivos primários e secundários os quais contribuem para o surgimento deste sinal. As causas secundárias são os próprios sinais motores da doença: tremor, rigidez, hipocinesia, acinesia e instabilidade postural. Já as causas primárias acontecem pelas desordens do controle central de movimento [3].O diagnóstico da DP acontece por meio de avaliações clínicas qualitativas as quais classificam a gravidade dos sinais da DP. Hoehn e Yahr (HY -Degree of Disability Scale), UPDRS (United Parkinson's Disease Rating Scale) and NUDS (Northwestern University Disability Scale) são algumas das escalas utilizadas na avaliação da doença.A escala mais utilizada no meio clínico é UPDRS [8], [9]. Essa escala é dividida em quatro partes, sendo que a parte 3 corresponde a avaliação motora dos sinais cardinais. A pontuação dessa escala varia de 0 a 4, no qual 0 representa normalidade e 4 maior grau de comprometimento. A bradicinesia na UPDRS é avaliada durante a execução do movimento de pinça, pronação/supinação e abrir e fechar a mão.Uma limitação desta escala é que seus resultados são bastante sensíveis à experiência e percepção do examinador. Então, com a finalidade em melhorar o diagnóstico da DP, trabalhos vêm sendo desenvolvidos para tornar a avaliação dos sinais cardinais mais objetivos.Uma grande parte destes estudos que avaliam a bradicinesia utilizam UMIs (unidades de medida inercial) [10], como: giroscópio, magnetômetro e acelerômetro, extraindo parâmetros da velocidade angular, variação do campo magnético e aceleração linear, respectivamente. Um dos grandes desafios destes estudos é identificar dentre os parâmetros extraídos quais possibilitam a melhor caracterização de normalidade e bradicinesia.Nesse sentido, este estudo tem como objetivo trazer uma revisão da literatura dos trabalhos que avaliam a bradicinesia, extraindo características dos sinais mensurados por sensores de medidas inerciais.

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“…This is then used as a basis for correlation to the UPDRS scores [35], [36]. The second approach is to extract sensor features and implement a regression/ classification model to minimise the prediction errors to the UPDRS scores [37]- [40]. Since there exists no single model that has been explicitly defined to correlate UPDRS scores across all motor symptoms, machine learning algorithms are typically used as tools of analysis [41], [42].…”

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A Heterogeneous Sensing Suite for Multisymptom Quantification of Parkinson’s Disease

Huo

Angeles

Tai

et al. 2020

IEEE Trans. Neural Syst. Rehabil. Eng.

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Parkinson's disease (PD) is the second most common neurodegenerative disease affecting millions worldwide. Bespoke subject-specific treatment (medication or deep brain stimulation (DBS)) is critical for management, yet depends on precise assessment cardinal PD symptoms-bradykinesia, rigidity and tremor. Clinician diagnosis is the basis of treatment, yet it allows only a cross-sectional assessment of symptoms which can vary on an hourly basis and is liable to inter-and intra-rater subjectivity across human examiners. Automated symptomatic assessment has attracted significant interest to optimise treatment regimens between clinician visits, however, no wearable has the capacity to simultaneously assess all three cardinal symptoms. Challenges in the measurement of rigidity, mapping muscle activity out-of-clinic and sensor fusion have inhibited translation. In this study, we address all through a novel wearable sensor system and machine learning algorithms. The sensor system is composed of a forcesensor, three inertial measurement units (IMUs) and four custom mechanomyography (MMG) sensors. The system was tested in its capacity to predict Unified Parkinson's Disease Rating Scale (UPDRS) scores based on quantitative assessment of bradykinesia, rigidity and tremor in PD patients. 23 PD patients were tested with the sensor system in parallel with exams conducted by treating clinicians and Manuscript

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Regression models for the quantification of Parkinsonian bradykinesia

Cited by 9 publications

References 13 publications

Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor

Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor

Uma Revisão Dos Métodos Para Avaliação Da Bradicinesia Parkinsoniana Utilizando Sensores Inerciais

A Heterogeneous Sensing Suite for Multisymptom Quantification of Parkinson’s Disease

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