Posts Tagged Accelerometer

[Abstract + References] Virtual Reality Game Development Using Accelerometers for Post-stroke Rehabilitation – Conference paper

Abstract

Stroke can generate several types of sequelae, including motor difficulties in both upper and lower limbs. One way to eliminate or reduce these difficulties is through physical therapy, but this type of treatment can often become tiresome and monotonous, decreasing the patient’s interest. Thus, aiming to assist in the rehabilitation of patients, this work seeks to use immersive virtual reality games with the purpose of interacting with physiotherapy exercises. In this type of game the individual must use special equipment (glasses) to feel in an environment where they can interact in different ways with the scenery. Among the possible equipment used for immersive virtual reality was chosen to use a smartphone in conjunction with a virtual reality glasses. In this way an environment was developed that allows the individual to move through the scenario by the control of the upper virtual members by accelerometry sensors, which will be positioned properly to identify the actual movement of the limbs. Thus, an equipment was developed capable of reading the movements and sending this information to a smartphone that executes the developed game.

References

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    Monteiro, A.: Qualidade de vida (QV) em Indivíduos com Sequelas de Acidente Vascular Cerebral (AVC). Vila Nova de Gaia: Escola Superior de Tecnologias da Saúde do Porto. Vila Nova de Gaia (2011)Google Scholar
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    Sha, M.A., et al.: EMG biofeedback based VR system for hand rotation and grasping rehabilitation. In: 14th International Conference on Information Visualisation (IV). IEEE, pp. 479–484 (2010)Google Scholar
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via Virtual Reality Game Development Using Accelerometers for Post-stroke Rehabilitation | SpringerLink

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[ARTICLE] Adaptation of a smart walker for stroke individuals: a study on sEMG and accelerometer signals – Full Text

ABSTRACT

Introduction:

Stroke is a leading cause of neuromuscular system damages, and researchers have been studying and developing robotic devices to assist affected people. Depending on the damage extension, the gait of these people can be impaired, making devices, such as smart walkers, useful for rehabilitation. The goal of this work is to analyze changes in muscle patterns on the paretic limb during free and walker-assisted gaits in stroke individuals, through accelerometry and surface electromyography (sEMG).

Methods

The analyzed muscles were vastus medialis, biceps femoris, tibialis anterior and gastrocnemius medialis. The volunteers walked three times on a straight path in free gait and, further, three times again, but now using the smart walker, to help them with the movements. Then, the data from gait pattern and muscle signals collected by sEMG and accelerometers were analyzed and statistical analyses were applied.

Results

The accelerometry allowed gait phase identification (stance and swing), and sEMG provided information about muscle pattern variations, which were detected in vastus medialis (onset and offset; p = 0.022) and biceps femoris (offset; p = 0.025). Additionally, comparisons between free and walker-assisted gaits showed significant reduction in speed (from 0.45 to 0.30 m/s; p = 0.021) and longer stance phase (from 54.75 to 60.34%; p = 0.008).

Conclusions

Variations in muscle patterns were detected in vastus medialis and biceps femoris during the experiments, besides user speed reduction and longer stance phase when the walker-assisted gait is compared with the free gait.

Keywords Stroke,sEMG,Smart walker,Gait,Accelerometer

INTRODUCTION

Stroke is considered a major health issue worldwide, since it is a leading cause of motor disabilities, affecting the independence and ability to perform daily tasks in most cases (Belda-Lois et al., 2011World…, 2015). There are two distinct types of stroke: the ischemic and the hemorrhagic. The first one is the most common and is responsible for 85-90% of cases, while the second type occurs in a smaller number (10-15%). In contrast, the mortality rate ranges from 8 to 12% for the ischemic type, while the hemorrhagic type has more fatal outcomes with numbers varying between 33% and 45% (Ovbiagele and Nguyen-Huynh, 2011).

Aside from the stroke type, the location and extension of the brain lesions may lead to different sequels (Deb et al., 2010) and, due to this reason there is a high heterogeneity among stroke sequels (Belda-Lois et al., 2011), varying according to the brain lesion location and extension. A lesion that occurs in the anterior cerebral artery, for example, may cause motor injuries predominantly in the lower extremity of the contralateral side, which interfere in the gait and body balance (Pare and Kahn, 2012).

Patients that had stroke usually have spastic muscles in the quadriceps femoris (vastus medialis, vastus lateralis, vastus intermedius and rectus femoris) and triceps surae (gastrocnemius medialis, gastrocnemius lateralis and soleus) while the hamstrings (biceps femoris, semitendinosus and semimembranosus) and tibialis anterior are flaccid, hindering the knee flexion and dorsiflexion (Murray et al., 2014Sheffler and Chae, 2015). In spite of flexor weakness, stroke individuals present more co-contractions between agonist and antagonist muscles when compared with healthy subjects (Shao et al., 2009), which occur in order to avoid knee and plantar hyperflexion.

All these conditions create a tendency on stroke individuals to produce a compensatory movement in order to walk, which is known as hip circumduction, typical in stroke gait (Whittle, 2007), causing an asymmetric gait, and overloading the non-paretic limb.

Due to this asymmetry and lack of balance, about 75% of stroke patients need assistance for walking independently during the first three months after stroke onset (Verma et al., 2012). However, there are no evidence-based criteria for choosing the device to help the patient (Verma et al., 2012). Tyson and Rogerson (2009) evaluated the use of cane and foot-ankle orthosis, which provided confidence and safety to the patients (20 stroke patients; mean age: 65.6 ± 10.4 years; mean time since stroke: 6.5 ± 5.7 weeks), improving their functional mobility. On the other hand, Suica et al. (2016) analyzed the immediate effect using a rollator, although for healthy subjects (19 subjects; 22 to 70 years), identifying a reduced muscle activity of the lower limbs (gluteus medius and maximus, rectus femoris, semitendinosus, tibialis anterior and gastrocnemius) caused by the weight bearing imposed on the walker.

Most stroke individuals need rehabilitation, whose main goal is the movement recovery to allow them to carry out daily tasks independently (Dohring and Daly, 2008Roger et al., 2011). This rehabilitation depends on many factors: lesion severity, age, type of therapeutic intervention, and how complex the stroke was. However, in many cases, rehabilitation does not provide an efficient recovery, and sometimes worsening the clinical status and the damage in the non-paretic limb. In such cases, those therapeutic interventions may provoke decreased mobility and secondary complications (Allen et al., 2011). On the other hand, conventional gait training and rehabilitation, commonly used nowadays, may not provide a total restoration for most patients (Dohring and Daly, 2008Suica et al., 2016).

Many studies (Cifuentes et al., 2014Dohring and Daly, 2008Tan et al., 2013) used robotic devices for motor rehabilitation, to recover important features of the gait and maintain muscle integrity. However, to the extent of our knowledge, no neuromuscular analysis was performed using robotic walkers applied for stroke rehabilitation. The main goal of this paper is to analyze changes in the muscle pattern on paretic limb during free and walker-assisted gaits in stroke individuals, through accelerometry and surface electromyography (sEMG). Another important goal is to verify the volunteer adaptation to a smart walker in the first contact. Therefore, this study is focused on the pattern-variation analysis of the paretic limb muscles and the swing and stance phase duration, in addition to the walking speed during the use of robotic walker and in free gait.

METHODS

Volunteers

Eight ischemic stroke individuals (4 males and 4 females; 65.75 ± 6.27 years old), from a rehabilitation institution of Espirito Santo state (Brazil), volunteered for the experiments. The number of volunteers generated a sample size for this study that has an effect size of 0.8, with statistical power of 50% and alpha equals 0.05. The research was previously approved by the Ethical Committee of Federal University of Espírito Santo (UFES/Brazil) and all volunteers signed the informed consent.

Eligibility criteria for inclusion in this study were: only one stroke that happened at least from 6 months up to 5 years before the tests; hemiparetic gait; Functional Ambulation Classification – FAC (Holden et al., 1984) in stage 2 or higher; ability to remain erect and with elbows at 90º while using the smart walker; age range from 50 to 80 years; enough cognitive skills and language to follow the experiment instructions. Individuals were excluded if they could not walk independently, had any musculoskeletal or neurological disorder limiting ambulation unrelated to the stroke, and if they had cardiorespiratory impairment, conditions that may prevent them from performing walking tests. Each volunteer was classified through a functional walking test (FAC) by the same physiotherapist, who has more than 20 years of experience.

sEMG and accelerometer data

All procedures for sEMG data acquisition and processing were based on recommendations of the “Standards for reporting EMG data” (Merletti and Torino, 2015). The kind of electrodes used was Ag/AgCl discoid shape, with 10 mm diameter, pre-gelled and with inter-electrode distance of 20 mm. Before the electrode placement, the skin was cleaned (alcohol 70%) and shaved to reduce impedance. Signals from four muscles of lower limb — vastus medialis (VM), biceps femoris (BF), tibialis anterior (TA) and gastrocnemius medialis (GM) — were acquired and analyzed. In addition, a reference electrode was placed on the medial malleolus. In all cases, the analyzed limb was the contralateral to the brain lesion. For better accuracy in electrode placement, two experts checked the electrode position placed on the muscles. Cables from the sEMG acquisition equipment were fixed on the limb using adhesive tape to minimize motion artifacts. In addition, a biaxial accelerometer was fixed using adhesive tape on the ankle of the contralateral limb, with the y-axis pointing cranially and x-axis pointing anteriorly.

Both sEMG and accelerometer data were recorded simultaneously using an acquisition equipment EMG 830C (EMG System do Brasil Ltda®) with 16-bit analog/digital conversion resolution, amplifier gain up to 2000V/V, common mode rejection > 100dB, input impedance of 109Ω, and maximum sampling frequency of 2 kHz. The measurement capacity ranged from -2000 to 2000 μV with sensitivity of 0.061 μV.

Smart walker

A smart walker from UFES/Brazil (Valadão et al., 2016) (Figure 1) was used in the experiments, which was built from a conventional four-legged walker adapted to a robotic mobile platform. The smart walker structure has forearm bars to provide weight support and comfort during its use, also allowing the user to guide it. The smart walker has also a height adjustment, which allows the user to stay in an upright posture. An onboard laser sensor is used to provide information about the distance from the walker to the user’s leg. By using the information provided by the laser sensor, the walker can adjust its speed through a proportional–integral–derivative controller (PID), with the goal of keeping the user at a predefined distance and angle, thus aiding him/her to maintain right posture (position and orientation) while using the device. […]

Figure 1 Smart Walker scheme: side view (left) and top view (middle). Stroke subject using the walker (right) in an experiment. Structure changes in the walker: (a) Handlebar; (b) Forearm support; (c) Stabilizer bars; (d) Laser sensor; (e) Pioneer 3-DX robot; (f) Free wheels; (g) Fixed distance (70 cm) from the user to laser sensor. 

 

Continue —> Adaptation of a smart walker for stroke individuals: a study on sEMG and accelerometer signals

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[ARTICLE] Validity of gait asymmetry estimation by using an accelerometer in individuals with hemiparetic stroke – Full Text PDF

Abstract.

[Purpose] The purpose of this study was to evaluate the validity of estimating step time and length asymmetries, using an accelerometer against force plate measurements in individuals with hemiparetic stroke.

[Subjects and Methods] Twenty-four individuals who previously had experienced a stroke were asked to walk without using a cane or manual assistance on a 16-m walkway. Step time and length were measured using force plates, which is the gold standard for assessing gait asymmetry. In addition to ground reaction forces, trunk acceleration was simultaneously measured using an accelerometer. To estimate step time asymmetry using accelerometer data, the time intervals between forward acceleration peaks for each leg were calculated. To estimate step length asymmetry using accelerometer data, the integration of the positive vertical accelerations following initial contact of each leg was calculated. Asymmetry was considered the affected side value divided by the unaffected side value.

[Results] Significant correlations were found between the accelerometer and the force plates for step time and length asymmetries (rho=0.83 and rho=0.64, respectively).

[Conclusion] An accelerometer might be useful for assessing step time and length asymmetries in individuals with hemiparetic stroke, although improvements are needed for estimating the accuracy of step length asymmetry.

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[ARTICLE] Wristband Accelerometers to motiVate arm Exercise after Stroke (WAVES): study protocol for a pilot randomized controlled trial – Full Text

Abstract

Background

Loss of upper limb function affects up to 85 % of acute stroke patients. Recovery of upper limb function requires regular intensive practise of specific upper limb tasks. To enhance intensity of practice interventions are being developed to encourage patients to undertake self-directed exercise practice. Most interventions do not translate well into everyday activities and stroke patients continue to find it difficult remembering integration of upper limb movements into daily activities. A wrist-worn device has been developed that monitors and provides ‘live’ upper limb activity feedback to remind patients to use their stroke arm in daily activities (The CueS wristband). The aim of this trial is to assess the feasibility of a multi-centre, observer blind, pilot randomised controlled trial of the CueS wristband in clinical stroke services.

Methods/design

This pilot randomised controlled feasibility trial aims to recruit 60 participants over 15 months from North East England. Participants will be within 3 months of stroke which has caused new reduced upper limb function and will still be receiving therapy. Each participant will be randomised to an intervention or control group. Intervention participants will wear a CueS wristband (between 8 am and 8 pm) providing “live” feedback towards pre-set movement goals through a simple visual display and vibration prompts whilst undertaking a 4-week upper limb therapy programme (reviewed twice weekly by an occupational/physiotherapist). Control participants will also complete the 4-week upper limb therapy programme but will wear a ‘sham’ CueS wristband that monitors upper limb activity but provides no feedback. Outcomes will determine study feasibility in terms of recruitment, retention, adverse events, adherence and collection of descriptive clinical and accelerometer motor performance data at baseline, 4 weeks and 8 weeks.

Discussion

The WAVES study will address an important gap in the evidence base by reporting the feasibility of undertaking an evaluation of emerging and affordable technology to encourage impaired upper limb activity after stroke. The study will establish whether the study protocol can be supported by clinical stroke services, thereby informing the design of a future multi-centre randomised controlled trial of clinical and cost-effectiveness.

Continue —> Wristband Accelerometers to motiVate arm Exercise after Stroke (WAVES): study protocol for a pilot randomized controlled trial | Trials | Full Text

Fig. 1 Study flow diagram

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[ARTICLE] Teaching Training Method of a Lower Limb Rehabilitation Robot – Full Text HTML

Abstract

This paper presents a new lower limb rehabilitation robot (hereafter, referred to as LLR-Ro) to help patients with lower limb disorder recover their movement function. Based on the ergonomics and kinematics principle, the motion of a human lower limb is analysed, which provides a theoretical basis for the leg mechanism design of LLR-Ro.

This paper also proposes a teaching training method for improving the training performance of LLR-Ro. When a physician trains the lower limb of a patient, the acceleration data of the patient’s lower limb motion will be collected through a wireless data acquisition system. The data can reproduce the movement trajectory of the physician rehabilitation training and this can be used as the training trajectory of LLR-Ro.

The experiment results of this study demonstrate that the teaching training method is feasible. The theory analysis and experimental research of LLR-Ro lay the foundations for the future clinical application of this method.

1. Introduction

Rehabilitation robotics is an application of robotic technology for people with limb disabilities [1, 2]. Elderly people are the most subject to cerebral vascular disease, hemiplegia and paraplegia. These diseases may cause limb motor dysfunction [3]. According to the statistics of the World Health Organization (WHO), by 2050, the world population of people over 60 will be double and the number of people disabled by disease will also increase [4]. Thus, there is an urgent increase in the demand for rehabilitation robots [5]. In recent years, research on rehabilitation robots has become an active topic [6, 7]. Several kinds of lower limb rehabilitation robots have been developed. These can be divided into trainers with single degree of freedom, wearable trainers, suspended gait trainers and sitting/lying gait trainers. As trainers with a single degree of freedom have a poor training effect and wearable trainers need the patient to be able to walk independently, this paper will only discuss suspended gait trainers and sitting/lying gait trainers.

Continue —> Teaching Training Method of a Lower Limb Rehabilitation Robot | InTechOpen

FIGURE 1. Lower limb analysis of an ordinary adult

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[WEB SITE] SignLanguageGlove gives voice to hearing and speech impaired

The SignLanguageGlove features a handful of sensors to convert hand and finger movements into text and spoken dialogue

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In an effort to further open the lines of communication for people with hearing and speech disabilities, a university student in London is developing a smart glove that converts sign language into text and spoken dialogue. Dubbed the SignLanguageGlove, the wearable device features a handful of sensors to convert hand and finger movements into words, with its creator now looking to add real-time language translation to the mix.

Designer and student at Goldsmiths, University of London Hadeel Ayoub is currently on the third iteration of her smart glove. Equipped with five flex sensors to monitor the bends and curves of each finger and an accelerometer to detect the orientation of the glove, the first experimental version took signs and turned them into visual letters on a screen.

She soon followed up with an improved model that was faster and more robust, featuring smaller, more discreet hardware and text that scrolled on a screen. The latest model features a text-to-speech chip with the hardware sewn into the lining of the glove.

She is now hard at work integrating a language translation function into the system. An Arabic, French and English speaker herself, Ayoub is looking to add Wi-Fi to the glove so that its motion can be relayed wirelessly to smartphones or tablets, where an app would handle the translation. She also plans to add a motion sensor for better mapping and develop a smaller version for children.

Gloves that turn sign language into audible dialogue is a concept that has been explored before. Back in 2009, the open-source AcceleGlove, which was intended for, among other things, interpreting sign language, was released. Then in 2012, a similar set of gloves took out the Microsoft Imagine Cup. But smartphones and tablets have come some way in that time, allowing for fresh takes on the concept.

Goldsmiths says that several companies have approached Ayoub with a view to mass producing the SignLanguageGlove, which would have an estimated cost of around £255 (US$385). But Ayoub says if it does come available as a commercial product, she hopes that schools and businesses will buy them for students, patients and employees with hearing and speech impairments.

Source: SignLanguageGlove gives voice to hearing and speech impaired

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[ARTICLE] Development of Serious Game for the Upper Arms Rehabilitation: “Balance Ball Rhythm Game” Case Study

Abstract

Accuracy, repeatability and activity are very critical factors for rehabilitation of hemiplegic patients. Rehabilitation exercise should be done regardless of space, time and cost.

Recently, interesting functional games, which induce active participation, have gained increasing attention. In the current study, a balance ball has been developed that can contract the user muscle and help in natural joint rotation by stimulating the upper arm muscle of hemiplegic patients. Additionally, a functional game was also developed that can engage the patients with rhythm game and training contents. The balance ball can detect the upper arm motion by an acceleration sensor and offered sense of reality and immersion with buttons and haptic sensors.

The game applied Fitt’s law to test accurate motion and two tutorial contents that induced their motion based on MFT. The level of difficulty can also be chosen to help intensive training for the motion with low scores from the tutorials and the patients can even do the upper arm rehabilitation exercise while listening to music.

via Development of Serious Game for the Upper Arms Rehabilitation: “Balance Ball Rhythm Game” Case Study – Springer.

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