scholarly journals RGB-D-Based Method for Measuring the Angular Range of Hip and Knee Joints during Home Care Rehabilitation

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 184
Author(s):  
Francesca Uccheddu ◽  
Rocco Furferi ◽  
Lapo Governi ◽  
Monica Carfagni

Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due to the patients’ lack of motivation and the doctors’ difficulty in carrying out rigorous supervision. The development of devices to assess the efficient recovery of the operated joint is highly valued both for the patient, who feels encouraged to perform the proper number of activities, and for the doctor, who can track him/her remotely. Accordingly, this paper introduces an interactive approach to angular range calculation of hip and knee joints based on the use of low-cost devices which can be operated at home. First, the patient’s body posture is estimated using a 2D acquisition method. Subsequently, the 3D posture is evaluated by using the depth information coming from an RGB-D sensor. Preliminary results show that the proposed method effectively overcomes many limitations by fusing the results obtained by the state-of-the-art robust 2D pose estimation algorithms with the 3D data of depth cameras by allowing the patient to be correctly tracked during rehabilitation exercises.

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Connie Schumacher ◽  
Darly Dash ◽  
Fabrice Mowbray ◽  
Lindsay Klea ◽  
Andrew Costa

Abstract Background Home care clients are typically older and have some degree of medical, physical, cognitive or social conditions that require formal or informal support to promote healthy aging in the community. Home care clients contribute a significant proportion of health service use, including emergency department visits. The DIVERT-CARE trial introduced a cardio-respiratory management model to improve client motivation, symptoms and rates of unwarranted health service use. Our objective was to explore the perceptions and experiences of individuals who participated in the DIVERT-CARE self-management support and education intervention. Methods A qualitative study was nested within a pragmatic randomized control trial and conducted following a 15-week multi-component cardio-respiratory intervention. A phenomenological descriptive design was employed using thematic analysis. Post-intervention, clients and their caregivers were invited to participate in a semi-structured telephone interview. Interview questions were designed to elicit the experience with the intervention components. Results A total of 29 interviews were completed from June 2018 to March 2020 from participants in Ontario, Newfoundland, and British Columbia. Three themes were identified; self-care trajectory and burden of responsibility, learning and behaviour change, and feeling connected pre-emptively to care providers, the information and medical advice, and connection through the therapeutic relationship. Conclusions Home care clients experience unique challenges in managing cardio-respiratory related chronic disease. Home-based interventions fostered a therapeutic relationship of connectedness while equipping clients with necessary knowledge and skills. These results inform recommendations for community nursing, and home-based self-management supports for older community-residing individuals.


2015 ◽  
Vol 8 (11) ◽  
pp. 113-126 ◽  
Author(s):  
Dung Duong Quoc ◽  
Jinwei Sun ◽  
Van Nhu Le

2021 ◽  
Author(s):  
Kamrie Sarnosky ◽  
Mark Benden ◽  
Leslie Cizmas ◽  
Annette Regan ◽  
Garett Sansom

Abstract Background: The COVID-19 pandemic has accelerated an already existing trend of individuals increasingly working remotely. With the growing popularity of remote working, specifically in a home office, there is a critical need to better understand and characterize the potential environmental differences between these two spaces. Indoor air pollution can have adverse health effects and impair cognitive functioning. Methods: This small pilot cohort study (N=22) recruited home and office workers to better understand the indoor air quality between these spaces. Air contaminants collected and assessed included PM10 and PM2.5, carbon dioxide (CO2), and total volatile organic compounds (TVOCs). Results: Findings showed a strong statistically significant increase in all measured variables within homes in comparison to traditional offices (p<0.001). For instance, The mean PM2.5 level in the traditional office space was 1.93 µg/m3 whereas it was more than twice this amount (5.97 µg/m3) in home offices.Conclusion: These results indicate that those who work from home are at increased risk due to longer exposures to higher levels of certain contaminants, the importance to better develop interventions to mitigate this reality is underscored by the fact that many workers will be moving to home-based offices in the coming years.


2019 ◽  
Author(s):  
Sang Hoon Chae ◽  
Yushin Kim ◽  
Kyoung-Soub Lee ◽  
Hyung-Soon Park

BACKGROUND Recent advancements in wearable sensor technology have shown the feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic has revealed the need and opportunity of internet-based wearable technology in future health care systems. Previous research has shown the feasibility of human activity recognition technologies for monitoring rehabilitation activities in home environments; however, few comprehensive studies ranging from development to clinical evaluation exist. OBJECTIVE This study aimed to (1) develop a home-based rehabilitation (HBR) system that can recognize and record the type and frequency of rehabilitation exercises conducted by the user using a smartwatch and smartphone app equipped with a machine learning (ML) algorithm and (2) evaluate the efficacy of the home-based rehabilitation system through a prospective comparative study with chronic stroke survivors. METHODS The HBR system involves an off-the-shelf smartwatch, a smartphone, and custom-developed apps. A convolutional neural network was used to train the ML algorithm for detecting home exercises. To determine the most accurate way for detecting the type of home exercise, we compared accuracy results with the data sets of personal or total data and accelerometer, gyroscope, or accelerometer combined with gyroscope data. From March 2018 to February 2019, we conducted a clinical study with two groups of stroke survivors. In total, 17 and 6 participants were enrolled for statistical analysis in the HBR group and control group, respectively. To measure clinical outcomes, we performed the Wolf Motor Function Test (WMFT), Fugl-Meyer Assessment of Upper Extremity, grip power test, Beck Depression Inventory, and range of motion (ROM) assessment of the shoulder joint at 0, 6, and 12 months, and at a follow-up assessment 6 weeks after retrieving the HBR system. RESULTS The ML model created with personal data involving accelerometer combined with gyroscope data (5590/5601, 99.80%) was the most accurate compared with accelerometer (5496/5601, 98.13%) or gyroscope data (5381/5601, 96.07%). In the comparative study, the drop-out rates in the control and HBR groups were 40% (4/10) and 22% (5/22) at 12 weeks and 100% (10/10) and 45% (10/22) at 18 weeks, respectively. The HBR group (n=17) showed a significant improvement in the mean WMFT score (<i>P</i>=.02) and ROM of flexion (<i>P</i>=.004) and internal rotation (<i>P</i>=.001). The control group (n=6) showed a significant change only in shoulder internal rotation (<i>P</i>=.03). CONCLUSIONS This study found that a home care system using a commercial smartwatch and ML model can facilitate participation in home training and improve the functional score of the WMFT and shoulder ROM of flexion and internal rotation in the treatment of patients with chronic stroke. This strategy can possibly be a cost-effective tool for the home care treatment of stroke survivors in the future. CLINICALTRIAL Clinical Research Information Service KCT0004818; https://tinyurl.com/y92w978t


Author(s):  
Aleksandra Rutkowska ◽  
Aleksandra Olsson ◽  
Jacek Namieśnik ◽  
Andrzej Milewicz ◽  
Jan Krzysztof Ludwicki ◽  
...  

Bisphenol A (BPA) is classified as an endocrine disruptor (ED) and it can interact with variety of hormone receptors leading to hormonal disruption and increased risk of various adverse health effects. Reducing human exposure to BPA is one of the main challenges of public health, as it is constantly present in daily life. A low-cost and commonly applied method to enable determination of BPA in the patient's body has yet to be developed. Currently available techniques are expensive, time-consuming, and require access to highly equipped analytical chemistry laboratories. Here we describe a fast and cheap engineered lateral flow assay of our design, to detect of BPA in urine samples. The technology not only provides an opportunity to perform rapid medical diagnostics without the need for an access to the central laboratory but also a means for self-diagnosis by the patient. The addition of β-glucuronidase improves the sensitivity of detection as it releases the free BPA from glucuronide complexes in urine. This invention may become a demonstrated analytical means for lowering human exposure to BPA and probably also to other EDs and consequently, may be useful in decrease of the risk for several lifestyle diseases.


2014 ◽  
Vol 971-973 ◽  
pp. 1304-1307
Author(s):  
Yi Wang Wang

Aiming at the applications of smart home, a novel intelligent remote control switch socket based on Wifi and PLC technologies was described and designed to replace the traditional wired sppliances.The intelligent remote control switch socket using Wifi and PLC communication technologies, compared to the existing technology solutions, which has the advantages of more flexible networking, low cost, easy to implement and promotion, etc..It will provide an intelligent switch socket design idea and method for the development and promotion of smart home system .


Author(s):  
Kalaiarasi Arumugam ◽  
L.Ashok Kumar

Today, brain attack disorders are one of the most life-threatening areas in the medical era, which mankind is facing nowadays. Globally, more than 10,000,000 people are subjected to brain attack disorders like hemiplegia and tremor, every year, where two-thirds of them survive. Among the survival community, more than 80 per cent of them are subjected to long-term impairment of their upper extremity. In order to treat the impairment, the survival group is subjected to medications and rehabilitation in order to improve their daily living. But the facilities are very limited in fast-developing countries like India when compared to western standards. The rehabilitation given corresponding with medications during the treatment period in hospitals does not give a complete recovery from disability. People from rural background could not meet their rehabilitation requirements even in the hospital during treatment and also when they are discharged to home after treatment from hospitals due to financial constraints and reachability. In order to motivate the survival group to fulfill their daily living and improve their lifestyle, this paper is focused on intelligent home-based rehabilitation system at low cost, reliability, and affordability. One major movement disorder namely Upper Arm Hemiplegia was taken into account and visited few major hospitals around Coimbatore and Chennai for literature and case study. The facilities available in various hospitals and their drawbacks were analyzed.Acupuncture & Electro-therapeutics Research E-pubBased on the studies conducted at hospitals and taking advice from therapists, an innovative low-cost home-based rehabilitation device using Electro-Hydraulic systems has been developed to support patients who were used to impaired living even after treatments. To support Upper Arm Hemiplegia patients, the devices which were developed and experimented to hold different functionalities are discussed in this paper.


2019 ◽  
Vol 38 (6) ◽  
pp. 973-980 ◽  
Author(s):  
Lisa I. Iezzoni ◽  
Naomi Gallopyn ◽  
Kezia Scales

Sign in / Sign up

Export Citation Format

Share Document