Identification of pointing difficulties of two individuals with Parkinson's disease via a sub-movement analysis

Salivia, Guarionex; Hourcade, Juan Pablo

doi:10.1145/1979742.1979636

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Fukamoto [35] describe una herramienta basada en juegos para procesos de rehabilitación de pacientes con problemas neurológicos; Geurts et al [36] describen el desarrollo de cuatro juegos orientados al tratamiento de pacientes con espasticidad (músculos tensos y rígidos) y pérdida del control motor, usando dispositivos como el Nintendo Wii y el Kinect™; Salivia y Hourcade [37] analizan el comportamiento de pacientes con la EP al manipular dispositivos de Interfaz Humano Computador (HCI, Human Computer Interface); y Göbel et al [38] se orientan hacia temas de entrenamiento y ejercicios físicos usando plataformas de juegos.…”

Section: Instrumentos De Medición De La Marchaunclassified

Automatización de pruebas clínicas para el diagnóstico y monitoreo de la enfermedad de Parkinson

Paredes¹,

Araujo²,

Cadavid³

et al. 2019

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Section: Instrumentos De Medición De La Marchaunclassified

Automatización de pruebas clínicas para el diagnóstico y monitoreo de la enfermedad de Parkinson

Paredes¹,

Araujo²,

Cadavid³

et al. 2019

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“…A previous case study with two individuals with Parkinson's disease [20] informed us of the necessity of personalizing the helping strategy provided by PointAssist. This necessity arises from our expectation of a high variability in performance from all individuals due to their differences in motor control as a result of their fine motor skills impairments.…”

Section: Research Goalmentioning

confidence: 99%

PointAssist

Salivia

Hourcade

2013

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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We tested PointAssist, software that assists in pointing tasks by detecting difficulty through a sub-movement analysis and triggering help, with adjustments proposed to personalize the assistance provided to individuals with motor impairments. A within-subjects study with sixteen individuals with fine motor skills impairments resulted in statistically significant effects on accuracy using Friedman's test with (χ 2 (1) = 6.4, p = .011) in favor of personalized PointAssist compared to no assistance.

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Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

Tian

Fan

et al. 2019

CCF Trans. Pervasive Comp. Interact.

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Daily monitoring of Parkinson's disease is important since clinical assessments can only provide a brief and limited view of a patient's condition. However, traditional approaches rely heavily on patients' self-reports or diaries, which are subjective and often lack of necessary details. In this work, we instrument a handle that can be attached to cutlery with inertial sensors to collect motion data unobtrusively. By analyzing the data of patients and normal people collected in the clinic, we demonstrated that our machine learning based model can not only distinguish between patients and normal people, but also identify the disease levels in a fine-grained manner. To further understand how the self-tracking data is used in clinic, we conducted a semi-structured interview with several clinicians. Through the interpretation from the perspective of both physicians and patients, we found that our handle can help the physicians better understand disease progression and promote patients' engagement in tackling the disease.

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Identification of pointing difficulties of two individuals with Parkinson's disease via a sub-movement analysis

Cited by 4 publications

References 7 publications

Automatización de pruebas clínicas para el diagnóstico y monitoreo de la enfermedad de Parkinson

Automatización de pruebas clínicas para el diagnóstico y monitoreo de la enfermedad de Parkinson

PointAssist

Monitoring motor symptoms in Parkinson’s disease via instrumenting daily artifacts with inertia sensors

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