Physiological motion monitoring: a wearable device and adaptative algorithm for sit-to-stand timing detection

Giansanti, Daniele; Maccioni, Giovanni

doi:10.1088/0967-3334/27/8/006

Cited by 40 publications

(39 citation statements)

References 29 publications

(19 reference statements)

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“…In [18], a review about the determinants that can influence the movement is presented. Different approaches used to estimate some of the spatio-temporal parameters typical of the movement are described, through devices equipped with accelerometers and gyroscopes, in [5], [19], [20] and, through devices based on accelerometers, in [21]- [23]. Moreover, the accuracy of an inertial approach to the measurement of the kinematics of arising from a chair with accelerometers and gyroscopes is discussed in [24].…”

Section: Preliminaries and Related Workmentioning

confidence: 99%

Automatic UPDRS Evaluation in the Sit-to-Stand Task of Parkinsonians: Kinematic Analysis and Comparative Outlook on the Leg Agility Task

Giuberti

Ferrari

Contin

et al. 2015

IEEE J. Biomed. Health Inform.

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Abstract-In this work, we first characterize the Sit-to-Stand (S2S) task, which contributes to the evaluation of the degree of severity of the Parkinson's Disease (PD), through kinematic features, which are then linked to the Unified Parkinson's Disease Rating Scale (UPDRS) scores. We propose to use a single body-worn wireless inertial node placed on the chest of a patient. The experimental investigation is carried out considering 24 PD patients, comparing the obtained results directly with the kinematic characterization of the Leg Agility (LA) task performed by the same set of patients. We show that (i) the S2S and LA tasks are rather unrelated and (ii) the UPDRS distributions (for both S2S and LA tasks) across the patients have a direct impact on the observed system performance.

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Section: Preliminaries and Related Workmentioning

confidence: 99%

Automatic UPDRS Evaluation in the Sit-to-Stand Task of Parkinsonians: Kinematic Analysis and Comparative Outlook on the Leg Agility Task

Giuberti

Ferrari

Contin

et al. 2015

IEEE J. Biomed. Health Inform.

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“…First, the mean and standard deviation (SD) of trunk angular velocity during the initial 1 s of each trial of activity were analyzed. Then, the start point of an activity was defined as whenever the trunk angular velocity deviates over 2 SD from the mean during the initial 1 s [17]. Similarly, the end point for that activity was defined as whenever the trunk angular velocity deviates more than 2 SD from the mean during the last 1 s.…”

Section: Apparatus and Proceduresmentioning

confidence: 99%

Trunk Angular Kinematics During Slip-Induced Backward Falls and Activities of Daily Living

Liu

Lockhart

2014

Journal of Biomechanical Engineering

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Prior to developing any specific fall detection algorithm, it is critical to distinguish the unique motion features associated with fall accidents. The current study aimed to investigate the upper trunk angular kinematics during slip-induced backward falls and activities of daily living (ADLs). Ten healthy older adults (age ¼ 75 6 6 yr (mean 6 SD)) were involved in a laboratory study. Sagittal trunk angular kinematics were measured using optical motion analysis system during normal walking, slip-induced backward falls, lying down, bending over, and various types of sitting down (SN). Trunk angular phase-plane plots were generated to reveal the motion features of falls. It was found that backward falls were characterized by a simultaneous occurrence of a slight trunk extension and an extremely high trunk extension velocity (peak average ¼ 139.7 deg/s), as compared to ADLs (peak average ¼ 84.1 deg/s). It was concluded that the trunk extension angular kinematics of falls were clearly distinguishable from those of ADLs from the perspective of angular phase-plane plot. Such motion features can be utilized in future studies to develop a new prior-to-impact fall detection algorithm.

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“…A single IS, worn on the lower back, has successfully been used for analyzing sub-phases and trunk kinematics during chair rise (Giansanti and Maccioni, 2006;Millor et al, 2013;Schwenk et al, 2012;Van Lummel et al, 2012;Van Lummel et al, 2013;Weiss et al, 2011Weiss et al, , 2010 and have been validated against other instrumentation for the sit-to-stand task (Boonstra et al, 2006;Janssen et al, 2008;Zijlstra et al, 2012). But Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/jbiomech www.JBiomech.com the validity of using an IS during the biomechanically challenging sit-to-walk (STW) task, which is common in daily life, has not yet been investigated (Kouta and Shinkoda, 2008).…”

Section: Introductionmentioning

confidence: 99%

The validity of assessing temporal events, sub-phases and trunk kinematics of the sit-to-walk movement in older adults using a single inertial sensor

Walgaard¹,

Faber

Lummel³

et al. 2016

Journal of Biomechanics

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a b s t r a c tThe aim of this study was to develop a method to identify temporal events, sub-phases and trunk kinematics of the sit-to-walk (STW) using a single inertial sensor (IS) worn at the lower back and to determine the validity of this method. Twenty-seven healthy older adults performed a STW movement, which started from sitting in a chair and included walking 3 m.Participants' movements were recorded with the IS, a reference measurement system consisting of an optical motion capture system (3 markers on the IS and one on each foot) and on-off switches located in the seat of the chair.Using the data from the IS and the reference measurement systems, the following signals and variables were calculated and compared: 3D IS motion (accelerations, velocities, displacements and angles), temporal events (start of trunk movement, seat-off, end of trunk flexion phase, end of trunk rising phase and gait initiation) and trunk kinematics (flexion range, maximum flexion velocity, maximum forward velocity and forward velocity during seat-off and at first heel-strike and maximum vertical velocity and vertical velocity at first heel-strike).For most variables acceptable differences (RMSE o 10%) were found between IS and reference measurement systems, except for sideways displacements and non-sagittal plane rotations. Furthermore, good results were found for temporal event detection, with ICC values for all variables being 0.988 or higher. With exception of the vertical velocity at heel-strike agreement for trunk kinematics was high, with ICC values being 0.867 or higher.

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Physiological motion monitoring: a wearable device and adaptative algorithm for sit-to-stand timing detection

Cited by 40 publications

References 29 publications

Automatic UPDRS Evaluation in the Sit-to-Stand Task of Parkinsonians: Kinematic Analysis and Comparative Outlook on the Leg Agility Task

Automatic UPDRS Evaluation in the Sit-to-Stand Task of Parkinsonians: Kinematic Analysis and Comparative Outlook on the Leg Agility Task

Trunk Angular Kinematics During Slip-Induced Backward Falls and Activities of Daily Living

The validity of assessing temporal events, sub-phases and trunk kinematics of the sit-to-walk movement in older adults using a single inertial sensor

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