Distribution of arm velocity and frequency of arm usage during daily activity: Objective outcome evaluation after shoulder surgery

Duc, Cyntia; Farron, Alain; Pichonnaz, Claude; Jolles, Brigitte M.; Bassin, Jean-Philippe; Aminian, Kamiar

doi:10.1016/j.gaitpost.2012.11.021

Cited by 22 publications

(25 citation statements)

References 24 publications

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“…Quantitative evaluation of arm usage and quality of movements in every kind of shoulder impairment contributes to outline a clinical picture about the functional recovery and the effectiveness of the treatment [30, 49]. Using the same number of IMU ( n = 3) and the same placement on both humeri and sternum, the shoulder function was evaluated before and after treatment, in patients underwent surgery for RC tear [5, 34]. Results showed significative differences in movements frequency between patients and control group during activities of daily life [5], with limited use of arm at 3 months after surgery [34].…”

Section: Discussionmentioning

confidence: 99%

“…However, despite their easy-to-use and wide application in clinical settings, these scores conceal an intrinsic subjectivity [2–4], inaccuracy in approaching diagnosis, follow-up and treatment of the pathologies. Quantitative and objective analyses are rapidly developing as a valid alternative to evaluate shoulder activity level, to gauge its functioning and to provide information about movement quality, e.g., velocity, amplitude and frequency [5, 6]. This interest in the use of measuring systems is growing in many medical fields to record information of clinical relevance.…”

Section: Introductionmentioning

confidence: 99%

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Wearable systems for shoulder kinematics assessment: a systematic review

Carnevale

Longo

Schena

et al. 2019

BMC Musculoskelet Disord

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BackgroundWearable sensors are acquiring more and more influence in diagnostic and rehabilitation field to assess motor abilities of people with neurological or musculoskeletal impairments. The aim of this systematic literature review is to analyze the wearable systems for monitoring shoulder kinematics and their applicability in clinical settings and rehabilitation.MethodsA comprehensive search of PubMed, Medline, Google Scholar and IEEE Xplore was performed and results were included up to July 2019. All studies concerning wearable sensors to assess shoulder kinematics were retrieved.ResultsSeventy-three studies were included because they have fulfilled the inclusion criteria. The results showed that magneto and/or inertial sensors are the most used. Wearable sensors measuring upper limb and/or shoulder kinematics have been proposed to be applied in patients with different pathological conditions such as stroke, multiple sclerosis, osteoarthritis, rotator cuff tear. Sensors placement and method of attachment were broadly heterogeneous among the examined studies.ConclusionsWearable systems are a promising solution to provide quantitative and meaningful clinical information about progress in a rehabilitation pathway and to extrapolate meaningful parameters in the diagnosis of shoulder pathologies. There is a strong need for development of this novel technologies which undeniably serves in shoulder evaluation and therapy.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wearable systems for shoulder kinematics assessment: a systematic review

Carnevale

Longo

Schena

et al. 2019

BMC Musculoskelet Disord

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“…Wearable sensors have also been used extensively for kinematic analysis of the upper limbs [15]. For example, it is possible to assess the progress of arm rehabilitation [16] and to monitor the effectiveness of shoulder surgery [17]. Due to their form factor and cost-effectiveness, they can also be used as an input for rehabilitation games [18].…”

Section: Introductionmentioning

confidence: 99%

Characterizing Human Box-Lifting Behavior Using Wearable Inertial Motion Sensors

Hlucny

Novak

2020

Sensors

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Although several studies have used wearable sensors to analyze human lifting, this has generally only been done in a limited manner. In this proof-of-concept study, we investigate multiple aspects of offline lift characterization using wearable inertial measurement sensors: detecting the start and end of the lift and classifying the vertical movement of the object, the posture used, the weight of the object, and the asymmetry involved. In addition, the lift duration, horizontal distance from the lifter to the object, the vertical displacement of the object, and the asymmetric angle are computed as lift parameters. Twenty-four healthy participants performed two repetitions of 30 different main lifts each while wearing a commercial inertial measurement system. The data from these trials were used to develop, train, and evaluate the lift characterization algorithms presented. The lift detection algorithm had a start time error of 0.10 s ± 0.21 s and an end time error of 0.36 s ± 0.27 s across all 1489 lift trials with no missed lifts. For posture, asymmetry, vertical movement, and weight, our classifiers achieved accuracies of 96.8%, 98.3%, 97.3%, and 64.2%, respectively, for automatically detected lifts. The vertical height and displacement estimates were, on average, within 25 cm of the reference values. The horizontal distances measured for some lifts were quite different than expected (up to 14.5 cm), but were very consistent. Estimated asymmetry angles were similarly precise. In the future, these proof-of-concept offline algorithms can be expanded and improved to work in real-time. This would enable their use in applications such as real-time health monitoring and feedback for assistive devices.

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“…Inertial measurement unit-based sensors attached to the trunk and/or limbs have also been used for physical activity monitoring in real-life conditions (13,(38)(39)(40)(41)(42)(43)(44)(45)(46). They are able to detect postural allocations (e.g., lying, sitting, standing) and to characterize the transition movements between postures (11,42,(47)(48)(49), estimated arm usage (50,51), and cervical mobility (52). Currently, continuous measurement (24 h/day) of up to 7 days and longer is feasible (41,53).…”

Section: Introductionmentioning

confidence: 99%

Technical and clinical view on ambulatory assessment in Parkinson's disease

et al. 2014

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With the progress of technologies of recent years, methods have become available that use wearable sensors and ambulatory systems to measure aspects of--particular axial--motor function. As Parkinson's disease (PD) can be considered a model disorder for motor impairment, a significant number of studies have already been performed with these patients using such techniques. In general, motion sensors such as accelerometers and gyroscopes are used, in combination with lightweight electronics that do not interfere with normal human motion. A fundamental advantage in comparison with usual clinical assessment is that these sensors allow a more quantitative, objective, and reliable evaluation of symptoms; they have also significant advantages compared to in-lab technologies (e.g., optoelectronic motion capture) as they allow long-term monitoring under real-life conditions. In addition, based on recent findings particularly from studies using functional imaging, we learned that non-motor symptoms, specifically cognitive aspects, may be at least indirectly assessable. It is hypothesized that ambulatory quantitative assessment strategies will allow users, clinicians, and scientists in the future to gain more quantitative, unobtrusive, and everyday relevant data out of their clinical evaluation and can also be designed as pervasive (everywhere) and intensive (anytime) tools for ambulatory assessment and even rehabilitation of motor and (partly) non-motor symptoms in PD.

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Distribution of arm velocity and frequency of arm usage during daily activity: Objective outcome evaluation after shoulder surgery

Cited by 22 publications

References 24 publications

Wearable systems for shoulder kinematics assessment: a systematic review

Wearable systems for shoulder kinematics assessment: a systematic review

Characterizing Human Box-Lifting Behavior Using Wearable Inertial Motion Sensors

Technical and clinical view on ambulatory assessment in Parkinson's disease

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