HeartHealth: A Cardiovascular Disease Home-based Rehabilitation System

Chatzitofis, Anargyros; Monaghan, David; Mitchell, Edmond; Honohan, Freddie; Zarpalas, Dimitrios; O’Connor, Noel E.; Daras, Petros

doi:10.1016/j.procs.2015.08.352

Cited by 26 publications

(21 citation statements)

References 8 publications

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“…The use of Kinect sensor has the advantages of portability and low cost which could lead to a home-based rehabilitation solution [4,6,7]. However, the lack of accuracy of joint kinematic estimation is one of the main obstacles for the use of this sensor in a clinical setting.…”

Section: Discussionmentioning

confidence: 99%

“…These facts led to the establishment of a new research field known as home based rehabilitation, as a complementary tool for therapeutic sessions. Furthermore, a new rehabilitation approach, known as exergames [3,4,5,6,7,8,9,10,11,12,13,14,15], has been proposed to help motivate patients while performing their rehabilitation tasks at home. This new concept incorporates games into the rehabilitation process, to add a motivational and challenging aspect to these programs.…”

Section: Introductionmentioning

confidence: 99%

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A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject’s movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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“…In this study, as in the study of Grace et al [50], adherence was defined as the number of sessions attended (in the case of this study according to the registration in the 'Exercise Diary') divided by the number of sessions prescribed (three sessions a week during 6 months in the case of this study). According to Chatzitofis et al [51] the application of home-based exercise programs in the context of CR carried the possibility of providing much higher adherence rates. Throughout the study/program, the adherence to the three weekly sessions was always higher than 65% in the two formats [43], a good adherence in both groups [43,50] however, with a noticeable decline in the last three months.…”

Section: Discussionmentioning

confidence: 99%

The effect of virtual reality on a home-based cardiac rehabilitation program on body composition, lipid profile and eating patterns: A randomized controlled trial

Vieira

Melo

Noites

et al. 2017

European Journal of Integrative Medicine

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Subjects with cardiovascular diseases are referred to cardiac rehabilitation, with a possibility of using virtual reality environments. The study aimed to analyze the effect of a home-based specific exercise program, maintenance phase, with a six months period, performed in a virtual reality (Kinect) or conventional (booklet) environment, on the body composition, eating patter ns and lipid profile of subjects with coronary artery disease. Methods: A randomized controlled trial was conducted with subjects from a hospital in Porto, Portugal. Subjects were randomly assigned to either intervention group 1 (n = 11), whose program encompassed the use of Kinect; or intervention group 2, a booklet (n = 11) or a control group, only receiving education concerning cardiovascular risk factors (n = 11) during 6 months. Beyond the baseline, at 3 and 6 months the body composition was assessed with a bioimpedance scale and a tape-measure, eating patterns with the semi-quantitative food frequency questionnaire and three months later, the lipid profile with laboratory tests. Descriptive and inferential statistical measures were used with a significance level of 0.05. Results: The intervention group 1 revealed significant improvements in the waist-to-hip ratio after 6 months (p = 0.033) and, between the baseline and third month, when compared with the control group (p = 0.041). The intervention group 1 also decreased their ingestion of total fat (p = 0.032) after six months and increased the high-density lipoprotein cholesterol (p = 0.017) 3 months after the program's conclusion. Conclusions: The virtual reality format had a positive influence on body composition, specifically on the waist-to-hip ratio, in the first three months.

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“…The system uses a camera and image recognition techniques to assess whether the patient is doing the rehabilitation exercises well or not. After this analysis, it provides feedback to the patient and their healthcare professionals [38].…”

Section: Context-awareness In Chronic Diseasesmentioning

confidence: 99%