Master
Small Devices, Big Data
Sensor technology is gradually transforming public health and is becoming of increasing interest in medical and clinical applications.
Translating big data collected from sensors into useful healthcare insights is of particular relevance. For instance, data from activity sensors and physiological sensors can be correlated with health information to identify health risks and problems. GRaCE-AGE, a project within the European Institute of Innovation and Technology (EIT) Health, is doing just that – employing sensor technology for the purpose of understanding, supporting and promoting healthy, active ageing.
GRaCE-AGE is a web-based mental-health support system utilizing medically validated sensors in monitoring and managing mental health risk and wellbeing in older adults. GRaCE-AGE is a derived from GRaCE (Galatean Risk and Care Environment), the enhanced and extended version based on Galatean Risk and Safety Tool (GRiST), which is a computer program containing mental health risk and safety expertise that has been developed with clinicians and patients over a period of fifteen years.
Data collected from one or more sensors is analysed and interpreted in the light of questions used by assessors for evaluating safety and wellbeing, which then simulates answers given by assessors. Table 1 shows a list of GRiST parameters and the sensor data output for such applications.
Using collated data input from older adults and various sensors, its inbuilt expertise will highlight any health or safety problems, compute a next course of action, and connect them to their care network to elicit help if necessary. This system aims to engage older adults while facilitating communication with people in their care network, clinical services and expert advice so that they are able to live safely and with a peace of mind.
With the rapid rise in the proportion of older people in society, there is an increasing concern to address the specific needs of this population. Maintaining mental, social, and physical health are as important in old age as in early years, and are important in prolonging independence and quality of life.
To find out more about sensor technology and its applications, contact us!
To find out more about GRaCE-AGE, click here.
Do pedometers do more harm than good?
Speaking at the annual meeting of the American Association for the Advancement of Science (AAAS) in Boston, Dr Greg Hager, professor of computer science at Johns Hopkins University, warned that obsessing over achieving the basic philosophy of 10,000 steps daily may lead people to chase over-ambitious goals and, as a result, do more harm than good.
Why 10,000 steps?
The leading expert pointed out that the target appears to be a relatively arbitrary figure. “Turns out in 1960 in Japan they figured out that the average Japanese man, when he walked 10,000 steps a day, burned something like 3,000 calories and that is what they thought the average person should consume. So they picked 10,000 steps as a number.”
Are pedometers recommended for monitoring physical activity?
Physical activity monitors or trackers, such as pedometers, have gained increasing popularity. When used appropriately, they serve a useful purpose by providing objective measures in activity and provide constant encouragement for people to move more. Pedometers can be a useful tool to create general awareness of activity levels by counting the number of steps taken. However, some users may become fixated on the “10,000-step rule”.
Should I be counting steps?
Rather than being fixated on reaching 10,000 steps a day using a pedometer, it can be used to track the average daily step count, then applied to setting appropriate goals. For a generally healthy individual looking to increase activity in daily routine, gradually increasing the number of steps may be a good way to start. While 10,000 steps per day may have a positive effect on health, it is important to note that the target is not based on science-based evidence. In addition, achieving 10,000 steps may not be feasible for everyone.
Are pedometers recommended for monitoring physical activity?
Relying solely on pedometers in measuring physical activity is unreliable. For one thing, it does not provide important measurement parameters such as duration and intensity. This highlights an important medical risk associated to the application of pedometers and consumer activity trackers in clinical applications.
Activity monitoring for research or clinical applications needs to be precise and validated. For this purpose, accelerometer-based activity monitors, such as the MOX, is used extensively. The MOX has been used to investigate the correlation of physical activity or sedentary behaviour to disease outcomes, as well as to monitor older adults and individuals with chronic conditions in the home and community settings. By customising accelerometer-based algorithms that accurately classify physical activity levels and/or posture such as sitting or lying for specific populations or individuals, reliable and valuable insights into real-world physical activity or movements can be obtained. Combined with activity goal settings, the activity monitor can be used to support translational care interventions. Furthermore, this information enables medical professionals to monitor and support their patients and provide more precise medical advice.
To find out more about the MOX Research system, click here.
Do you have ideas for physical activity monitoring? Feel free to contact us and discuss your ideas!
Associations of physical activity & sedentary behavior with quality of life in colorectal cancer survivors
Background
Population ageing and increasing survival rates of colorectal cancer patients are leading to an increasing number of colorectal cancers survivors worldwide. Many of these individuals experience long-lasting side effects due to the cancer or its treatment, such as bowel problems or fatigue, which can severely impact their quality of life. Increasing physical activity and reducing sedentary behavior have been proposed as means to improve health and functioning of colorectal cancer survivors, but there is still a paucity of research on this topic. Consequently, there are no specific guidelines on physical activity and sedentary behavior available for colorectal cancer survivors to date. Within her PhD research, Eline van Roekel has applied a bio-psychosocial approach to study associations of physical activity and sedentary behavior with quality of life in colorectal cancer survivors. She observed that next to higher levels of moderate-to-vigorous physical activity, more light intensity physical activity and less sedentary behavior were associated with better quality of life outcomes in colorectal cancer survivors. This provides important leads for further research on these new potential targets for lifestyle interventions for this population.
Study design
For this PhD research, data were used from the Energy for life after ColoRectal cancer (EnCoRe) study. This observational study was initiated by Eline van Roekel and her supervisors at the Department of Epidemiology at Maastricht University, in collaboration with medical specialists and nurse practitioners at the Maastricht UMC+. The aim of the EnCoRe study is to investigate associations of lifestyle factors, including diet, physical activity and body composition, with quality of life in colorectal cancer survivors. During the design and conduct of this study, a bio-psychosocial conceptual approach has been applied based on the International Classification of Functioning, Disability and Health developed by the World Health Organization. Thereby, quality of life and functioning is being measured and analyzed in a comprehensive way, by including physical aspects of health as well as psychosocial aspects and the ability of individuals to participate in society.
The EnCoRe study consists of an ongoing prospective study, in which colorectal cancer patients are being included at diagnosis and followed up until 2 years post-treatment (Figure 1). Repeated measurements of several lifestyle factors and quality of life outcomes are performed. To also study the survivorship trajectory after 2 years post-treatment, a complementary cross-sectional study was conducted in 2012 in 155 individuals, who had been diagnosed with stage I-III colorectal cancer between 2002 and 2010 at the Maastricht UMC+. Within these individuals, several measurements were performed at one point in time and these data were used for the results presented in the thesis of Eline van Roekel.
Design of the prospective and cross-sectional part of the Energy for life after ColoRectal cancer (EnCoRe) study. Data of the cross-sectional part were used for the research described in the PhD thesis of Eline van Roekel.
Main results
The overall aim of this PhD thesis was to study associations of physical activity and sedentary behavior (i.e. sitting or lying at low energy expenditure during waking hours) with quality of life in colorectal cancer survivors. The quality of life outcomes there were studied comprised global quality of life, physical functioning, role functioning (i.e. the ability to perform normal daily activities), social functioning, disability, fatigue and distress. A qualitative overview of the results is provided in Table 1.
First of all, associations were studied of self-reported physical activity with quality of life outcomes. In particular, Eline van Roekel studied associations of light physical activity (e.g. light household work) and moderate-to-vigorous physical activity (e.g. cycling and heavy household work) with quality of life. She observed that more self-reported time spent in both light and moderate-to-vigorous physical activity were associated with better physical functioning. In addition, more time spent in light physical activity was also associated better role functioning and less disability.
Besides self-reported physical activity, levels of sedentary behavior and physical activity were measured using the MOX activity monitor (Maastricht Instruments, B.V.). The participants wore the tri-axial MOX monitor, attached with a plaster on the anterior thigh, 24 hours/day for seven consecutive days. Data were obtained on daily time spent in sedentary behavior, standing and physical activity. In addition, it was determined how much daily time was spent in prolonged uninterrupted periods (bouts) of sedentary time of at least 30 minutes, as well as the usual duration of sedentary bouts. Eline van Roekel observed that more time spent in total and prolonged sedentary behavior and longer usual bout duration were associated with a lower reported level of physical functioning, and higher levels of disability and fatigue. She also found that more prolonged sedentary time and longer usual bout duration were associated with worse global quality of life and role functioning.
To be able to eventually develop effective lifestyle interventions to reduce sedentary behavior, it is important to study by what type of activity sedentary behavior should be replaced (substituted). For that purpose, Eline van Roekel applied a statistical technique (isotemporal substitution modelling) to model the substitution of 1 hour/day of sedentary behavior with 1 hour/day spent standing or in physical activity, and to investigate how these substitutions were associated with quality of life of colorectal cancer survivors. She found that substituting sedentary time with standing or physical activity was associated with better physical functioning. In addition, substitution of sedentary time with standing was associated with less disability and fatigue.
| Table 1. Qualitative summary of main findings described in Eline van Roekel’s PhD thesis, regarding associations of levels of physical activity and sedentary behavior with quality of life outcomes in stage I-III colorectal cancer survivors, 2-10 years post-diagnosis | |||||||
| Global quality of life | Physical functioning | Role functioning | Social functioning | Disability | Fatigue | Distress | |
| Self-reported physical activity | |||||||
| Light physical activity | 0 | + | + | 0 | – | 0 | 0 |
| Moderate-to-vigorous physical activity | 0 | + | 0 | 0 | 0 | 0 | 0 |
| Sedentary behavior assessed with activity monitor data | |||||||
| Total sedentary time | 0 | – | 0 | 0 | + | + | 0 |
| Prolonged sedentary timea | – | – | – | 0 | + | + | 0 |
| Usual sedentary bout durationb | – | – | – | 0 | + | + | 0 |
| Isotemporal substitution modelling with activity monitor data | |||||||
| Substituting sedentary time with equal time in standing | 0 | + | 0 | 0 | – | – | 0 |
| Substituting sedentary time with equal time in physical activity | 0 | + | 0 | 0 | 0 | 0 | 0 |
Key: [+]significant positive association, [-]significant negative association, [0]no significant association.a Average time spent in sedentary bouts with ≥30 minutes duration per day.b Bout duration at which 50% of total sedentary time is accrued.
Conclusion
Altogether, the results of this PhD research indicate that next to increasing moderate-to-vigorous physical activity, increasing light physical activity and reducing sedentary behavior may be promising new avenues for lifestyle interventions aiming to increase quality of life in colorectal cancer survivors. Further research in the prospective part of the EnCoRe study will be necessary to study whether changes in physical activity and sedentary behavior are also associated with clinically relevant changes in quality of life outcomes. In addition, more research is needed on the underlying biological mechanisms mediating associations of physical activity and sedentary behavior with quality of life outcomes in colorectal cancer survivors.
Eline van Roekel defended her PhD thesis ‘Energy for life after colorectal cancer: Associations of physical activity and sedentary behavior with quality of life outcomes in colorectal cancer survivors’ on 15 December 2015 at Maastricht University. This PhD project was funded by the Stichting Alpe d’HuZes within the research program ‘Leven met kanker’ of the Dutch Cancer Society, the Dutch Cancer Society and by the GROW School for Oncology and Developmental Biology. The EnCoRe study is also supported by Kankeronderzoekfonds Limburg (part of Health Foundation Limburg).
For more information about the EnCoRe study: http://encorestudie.nl/.
Reference
Associations of sedentary time and patterns of sedentary time accumulation with health-related quality of life in colorectal cancer survivors
Eline H. van Roekel, Elisabeth A.H. Winkler, Martijn J.L. Bours, Brigid M. Lynch, Paul J.B. Willems, Kenneth Meijer, IJmert Kant, Geerard L. Beets, Silvia Sanduleanu, Genevieve N. Healy, Matty P. Weijenberg. Preventive Medicine Reports v4 nSuppl. 4 (201612): 262-269
Eline van Roekel, PhD
Postdoctoral Researcher
EnCoRe. Study Dept. Epidemiology / Grow School for Oncology and Developmental Biology
EU Falls Festival 2017 - Insights on physical activity monitoring
On May 8 and 9 2017, the annual European Falls Festival was held at the Amsterdam Medical Centre, with the theme “Developing Collaborations across Professions and throughout Europe”. Leading multi-disciplinary professionals were brought together at the highly respected conference to discuss the research and innovation in the study and implementation of falls prevention in older people. The Accelerometry.eu team was present to exhibit our latest products, including the MOX accelerometry sensor. The topic of “fall technologies”, which can be classified in four domains: fall detection, fall assessment, fall prediction and fall intervention, were addressed in many presentations. Wearable physical activity monitoring technologies were highlighted in many presentations. An overview of interesting topics is included below:
Physical activity monitoring
Being physically active in a safe manner
Valpreventie.be provides useful information on fall prevention methods and strategies for older persons and caregivers. The theme of the national Belgian Fall Prevention Week was “Stay Active, Do It Safe”. On being safe while staying physically active, topics relevant to daily physical activities were brought to attention. These include footwear, vision, medication, dizziness, food and home/environment safety. Physical activity monitors with fall detection algorithms can be used to detect falls and provide additional safety by calling for help if appropriate.
After hospital discharge
Bianca Buurman, Professor of Transitional Care at the Amsterdam Medical Centre, highlighted the importance of early mobilization and physical activity 10-15 days following hospital discharge. There is a potential for eHealth activity monitoring tools to support transitional care interventions. By encouraging appropriate physical regimens in transitional care, the long term risk of falls due to functional decline may be reduced.
Novel technologies for successful fall prevention
Luca Palemerini, Research Fellow at the University of Bologna and Adjunct Professor of the Biomedical Signals & Data Processing course of the Master degree in Electronic Engineering, provided a stimulating overview of technology for fall detection and fall risk estimation using wearable sensors and data mining. The opportunities for wearable accelerometers are:
- fall risk assessment
- activity monitoring
- intervention / fall prevention trainig
- assisted living
for more information about MOX Accelerometry or accelerometer-based algorithms.
Optimal placement of accelerometers for fall detection in the elderly
Fall detection in the elderly
Falls are a major public health problem in the elderly and is a leading cause of unintentional injury and deaths in the elderly population worldwide. A fall episode can have profound implications on their independence, health and overall quality of living, imposing additional socio-economic burdens. Many complications from an unattended fall could be prevented if prompt help was received or properly detected in situations of daily life. Over the years many fall detection devices have been proposed for the elderly, but many do not provide an effective solution. The most promising angle of fall detection seems to be the use of accelerometers. However, there are many different approaches on placement of accelerometers for fall detection, and it seems uncertain which one is preferable. Generally, there are a few evaluation criteria and consideration factors.
Criteria of fall detection systems
The placement site can largely affect the four possible situations of a fall detection system (Noury, N., et al.):
- true positive (TP), a fall occurs and the system correctly detects it;
- false positive (FP), the system declares a fall event, but it did not occur;
- true negative (TN), a normal fall-like movement is performed, the device does not declare a fall;
- false negative (FN), a fall occurs, but the system does not detect it.
Three criteria are proposed to evaluate the reliability of a fall detection system (Abbate S., et al.):
- sensitivity = TP/(TP + FN), the ability to detect all real falls;
- specificity = TN/(TN + FP), the ability to detect only real falls;
- accuracy = (TP + TN) /(TP + FP + FN + TN), which is the proportion of true results in the considered data set
Aside from the capacity of the fall detection system, usability is also often considered as it is a fundamental factor for real adoption of a fall detection system.
Review of accelerometer placement strategies
A brief review on promising accelerometer placement strategies in present literature was performed by a current student from Maastricht University as part of Masters coursework. Three studies stood out when validity was compared based on three attributes: sensitivity, specificity and usability.
Study #1 (Kangas M., et al.)
The first study used three sensors (forehead, waist and wrist), which achieved a specificity and sensitivity of 100% and 98% respectively. When the data gathered by the wrist sensor was excluded, reliability was only slightly lower. Despite a high validity, the placement of a sensor on the forehead makes this an undesirable option for use in daily life.
Study #2 (Gjoreski H., et al.)
The second study used four sensors (sternum, waist, thigh and ankle; and found a specificity and sensitivity of 99% and 97.8% respectively. This sensor placement would probably be preferable to the one used by Kangas as it is less obtrusive. However, it would require regular replacement of four sensors which likely lead to low compliance, hence defeats the purpose of using this placement strategy for accurate fall detection.
Study #3 (Abbate S., et al.)
Lastly, the third fall detection system included a smartphone-based setup. It was found that data from a single sensor on the thigh analysed by the smartphone, in conjunction with the smartphone’s integral accelerometer, achieved a specificity of 100% but a relatively low sensitivity of 96.3%. When using only the smartphones integral sensor without an additional sensor, both sensitivity and specificity were too low to qualify as accurate fall detection. The disadvantage of using the smartphone for fall detection in the study is the need to be carried (within range of 3 meters) and to remain charged at all times. This is not always feasible. Furthermore, carrying a smartphone enables the individual to contact relatives or caregivers for assistance in the event of emergency if a fall should happen. In this context, the possibility of using a small external sensing unit can greatly reduce the intrusiveness of the system.
Conclusion
The author concluded that there is currently no clear optimal placement that will outperform the others in every situation. For home use, the smartphone based setup would likely have the populations’ preference, although there is a high chance of the phone being out of reach when it is most needed, when compared to accelerometer-only setups. For research purposes the placements used by Kangas and Gjoreski would have the upper hand based on sensitivity, although gathering subjects for field research may be easier when only one sensor and a Smartphone are required.
Comments
The proposed placement strategies and accelerometers for fall detection in the elderly are numerous, and reliability may be comparable. However, fall detection systems based on wearable sensors are reliant on user compliance (remembering to wear the device and choosing to wear the device). Therefore, it is expected that systems with multiple sensors will be less favourable and result in lower compliance in the elderly.
Fall detection systems with single sensors placed on the torso is the most common, as revealed revealed in a systematic review (Chaudhuri et al., 2014). Illustration on the right shows the sensitivity and specificity of such systems with respect to the sensor location. Devices placed on the torso had a sensitivity and specificity with a median sensitivity and specificity of 97.5% (81–100%) and 96.9% (77–100%) respectively (Chaudhuri et al., 2014). Whereas, devices placed around the head and limbs had a lower median sensitivity and specificity of 81.5% (70.4–100%) and 83% (80–95.7%) respectively. Those involving multiple sensors had a median sensitivity of 93.4% (range 92.5–94.2) and a median specificity of 99.8% (range of 99.3–100).
Although many fall detection systems show high sensitivity and specificity in simulated research settings, it is important to take note that it may not reflect the same reliability in real-world situations. As algorithms are optimized to the test situation, real-world tests would be a more rigorous indicator of the device’s reliability. However, few have been performed. Therefore, more real-world tests may be necessary to prove the efficiency of these systems before implementing it as a feasible solution for fall detection in the elderly.
References
Abbate S, Avvenuti M, Bonatesta F, Cola G, Corsini P, et al. A smartphone-based fall detection system. Pervasive and Mobile Computing. Vol 8 (6). Dec 2012.
Gjoreski H, Lustrek M, Gams M. Accelerometer Placement for Posture Recognition and Fall Detection. Intelligent Environments. 2011.
Kangas M, Konttila A, Lindgren P, Winblad I, Jamsa T, et al. Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait & Posture. Vol 28 (2). Aug 2008.
Noury, N., Rumeau, P., Bourke, A. K., ÓLaighin, G., & Lundy, J. E. (2008). A proposal for the classification and evaluation of fall detectors. Irbm, 29(6), 340-349
Acknowledgements
The review of accelerometer placements in the current literature was contributed by Gerard van der Linden, a current Masters student in Maastricht University’s Faculty of Health, Medicine and Life Sciences (FHML).
for more information about MOX Accelerometry or fall detection algorithms.
Quantifying free-living sedentary behaviour using activity monitors
Assessing physical activity
Quantifying physical activity, or lack thereof, have been used to analyse sedentary behaviour in order to understand physical activity and disease outcomes, as well as define the effectiveness of intervention strategies. Physical activity has previously been assessed by means of self-reported measures such as questionnaires and interviews, especially in larger population studies. However, such self-reported measures can report bias in the study. With advancement in technology, wearable activity monitors are increasingly being used to objectively quantify free-living sedentary behaviour. Furthermore, they are generally small, lightweight, portable, non-invasive and unobtrusive.
The study
A recent large population study (2,497 individuals) published in the journal Diabetologia on 2 February 2016 (1) was one of such studies undertaken to measure free-living sedentary behaviour using wearable activity monitors. The study, led by first author Julianne van der Berg and senior author Annemarie Koster from Maastricht University, looked at the amount and patterns of sedentary (sitting or reclining) behaviour in relation to type 2 diabetes and the metabolic syndrome. It was performed within The Maastricht Study, an extensive phenotyping study of adults that focuses on the etiology of type 2 diabetes and its complications and comorbidities.
Results
The study participants with Type 2 Diabetes spent less time stepping and had less moderate intensity activity but the most significant risk factor is the increased time spent sedentary (sitting/lying). It was concluded that an extra hour of sedentary time was associated with a 22% increased risk for type 2 diabetes and 39% increased risk for the metabolic syndrome. These results suggested that sedentary behaviour may play a significant role in the development and prevention of type 2 diabetes.
Fig. 1 Time (hours) spent in primary daily activities according to glucose metabolism status. (Adapted from van der Berg et al., 2016) (1)
Activity monitors
There are activity monitors that have been developed for research purposes and more specifically, for accurately distinguishing sedentary behavior. The Glasgow-based PAL Technologies’ activPAL™ activity monitor was chosen by the researchers in the Maastricht Study. Similarly, the MOX activity monitor has proven high accuracy in determining free-living physical activity behavior and assessing different activity intensities in healthy and chronically ill patients (chronic obstructive pulmonary disease, type 2 diabetes or mitochondrial disease) (2, 3). Furthermore, the MOX activity monitor is waterproof and can be adhered directly to the skin on the thigh 24/7 for 8 days by a patch. Using accurate, reliable and objective activity monitors is an advantage as advances in accelerometry technology have allowed low power consumption, easy setup, and unobtrusive design to provide a promising tool for monitoring free-living physical activities.
Click here to the article by van der Berg et al. published online in the journal Diabetologia, 2016.
REFERENCES
- van der Berg JD, Stehouwer CDA, Bosma H, van der Velde JHPM, Willems PJB, Savelberg HHCM, et al. Associations of total amount and patterns of sedentary behaviour with type 2 diabetes and the metabolic syndrome: The Maastricht Study. Diabetologia. 2016;59(4):709-18.
- van der Weegen S, Essers H, Spreeuwenberg M, Verwey R, Tange H, de Witte L, et al. Concurrent Validity of the MOX Activity Monitor Compared to the ActiGraph GT3X. Telemedicine and e-Health. 2015;21(4):259-66.
- Koene S, Dirks I, van Mierlo E, de Vries PR, Janssen AJWM, Smeitink JAM, et al. Domains of Daily Physical Activity in Children with Mitochondrial Disease: A 3D Accelerometry Approach. Berlin, Heidelberg: Springer Berlin Heidelberg. p. 1-11.
For more information about The Maastricht Study:
https://www.demaastrichtstudie.nl/research
For further information about the Maastricht Study, please contact :
Anniemarie Koster
Associate Professor
Associate Professor Programme: Inequity, Participation and Globalisation (IPG)
Sociale Geneeskunde, School for Public Health and Prim Care, Fac. Health, Medicine and Life Sciences
Exercise Does Not Negate the Harmful Effects of Inactivity
Exercise is healthy, but an hour per day cannot fully compensate for the negative effects of excessive sitting and inactivity during the rest of the day.
It is generally known that exercise is beneficial for health and in reducing the risk of metabolic diseases such as diabetes and cardiovascular diseases. Unfortunately, many adults do not reach the current physical activity guidelines (150 minutes of moderate to vigorous physical activity per week). Moreover, we sit too much. In the car/bus on the way to work, at work behind our desk and at home in front of the television or computer. Inactivity, especially excessive sitting, is a major implicator of metabolic diseases and has been branded the “new smoking” for its supposed health risks. Whether this statement is true is inconclusive based on current research, but one thing most researchers do agree: too much sitting is unhealthy.
Decreasing sitting time by moving more and fitting physical activity into your day is one way to get started. Other than a bout of exercise a day, an easy alternative is to increase movement in our daily activities, such as housework, gardening, walking or cycling as a mode of commute and taking the stairs. A recently published study by Duvivier et al. (in scientific journal Plos One) suggested that one hour of daily physical exercise cannot fully compensate for the negative effects of inactivity on risk factors for cardiovascular disease (insulin level and plasma lipids) if the rest of the day is spent sitting.
The Study
In this study, eighteen healthy young subjects, age 21±2 year old of normal BMI followed one of three randomly assigned physical activity regimes for four days. In the sitting regime, participants were instructed to sit 14 hr/day. In the exercise regime, participants were instructed to sit 13 hr/day and to substitute 1 hr of sitting with 1 hr of vigorous supervised bicycling. Lastly, participants in the minimal intensity physical activity regime were instructed to substitute 6 hrs sitting with 4 hr walking and 2 hr standing. All regimes were instructed to walk 1 hr/day, stand 1 hr/day and spend 8 hr/day sleeping or supine. The exercise and minimal intensity physical activity regime had the same daily energy expenditure. During the four days of regime, physical activity monitors were continuously worn (24 hours a day) by the participants.
Figure 1. Time spent on different activities per regime.
Graphical overview of the three regimes followed by the participants and time spent in different activity categories (sleeping, sitting, standing, cycling and activity (walking).
Results
Results of the study showed that reducing inactivity by increasing the time spent walking/standing is more effective in lowering blood cholesterol and lipid levels, when energy expenditure is kept constant. Moving more everyday and reducing prolonged sitting time is much more effective than a bout of one hour intensive cycling exercise. It also demonstrated that the negative effects of extensive sitting on our health cannot be compensated by an hour of exercise per day. Therefore apart from including exercise in our lifestyle, health advice should also focus on decreasing sedentary time and moving more.
One of the strategies to keep track of daily movements is the use of an activity tracker. Physical activity trackers have gained popularity to assist individuals in monitoring their level of activity and reaching their daily activity goals.
Reference:
Duvivier BMFM, Schaper NC, Bremers MA, van Crombrugge G, Menheere PPCA, Kars M, et al. (2013) Minimal Intensity Physical Activity (Standing and Walking) of Longer Duration Improves Insulin Action and Plasma Lipids More than Shorter Periods of Moderate to Vigorous Exercise (Cycling) in Sedentary Subjects When Energy Expenditure Is Comparable. PLoS ONE 8(2): e55542.
Download the article here.
For more information about this study, please contact:
Bernard Duvivier, MD
Department of Internal Medicine
Department of Human Movement Sciences
Maastricht University Medical Centre
Maastricht, The Netherlands
bernard.duvivier@maastrichtuniversity.nl
MOX eHealth activity sensor helps increase physical activity in COPD and diabetes patients
Physical activity is important for maintaining quality of life in patients with chronic conditions. Physical activity reduces the amount of complications, exacerbations and required medication intake and has a positive effect on mood and energy level. For patients with COPD or diabetes, being sufficiently active is often difficult due to shortness of breath or overweight. Changing the behavior of these patient often proves challenging, as it has become embedded in an established lifestyle. Today’s health care providers are especially in need of effective strategies to coach these patients towards long-term increases in physical activity. Among the most effective interventions today are setting and revising behavioral goals, giving advice and self-monitoring. However, these methods require reliable data on the patient’s behavior, which are presently difficult to obtain. Consequently, care providers are spending valuable time and effort to collect information, often gathered from subjective reports. Shortly, there is a need for easy and accurate feedback on patients’ physical activity levels.
This has inspired the creation of a new tool: It’s LiFe!, the Interactive Tool for Self-management through Lifestyle Feedback. Its development has been a combined effort of Maastricht University, e-Health specialist Sananet and the mHealth developers of Maastricht Instruments. The tool consists of the MOX accelerometer, which is wirelessly connected to a smartphone and an online coaching system. Objective data on the amount of physical activity in relation to personal targets is measured by the wireless accelerometer and made available to the patient through an app and website.
The tool is embedded in a counselling program that consists of feedback and face-to-face coaching sessions from a doctor's nurse. Doctors' nurses can monitor their patients' physical activity through the coaching system from within the family doctor's office. The effectiveness of this approach has been evaluated in the dissertation of Sanne van der Weegen and Renée Verwey. Results of their studies are promising: The combined intervention of the coaching tool and doctor’s nurse support increases daily physical activity with 11 minutes in COPD and diabetes patients, in comparison to the regular care process. Patients and doctors’ nurses rated the intervention as highly positive.
The MOX eHealth accelerometer
The flexibility of the wireless MOX accelerometer greatly facilitated the development of an intervention, which had to be tailored to the specific needs of the patient group and caregivers. This required adaptability of the accelerometer algorithms and communication of the physical activity data with the other systems involved. In addition, there is research data to support the validity of the MOX eHealth accelerometer. The MOX shows high correlation to gold standards in treadmill protocols. The wireless physical activity sensor shows good correlation in daily living activities compared to the Actigraph GT3X, which is widely used in clinical research and known to correlate well with indirect calorimetry measures.
Measurement and promotion of physical activity
Sufficient physical activity is essential for cardio-metabolic health and quality of life. However, inactivity and sedentary behavior such as sitting, which is associated to an array of health risks, is prevalent in our current way of living. Promotion of physical activity is therefore crucial.
Research into the promotion of physical activity has revealed that altering one’s lifestyle or losing excess weight can be challenging and is often accompanied by barriers. Practice nurses, physiotherapists and dieticians can provide support in making lifestyle changes. One of the combined strategies aimed at increasing physical activity is adding group sessions, however it is uncertain whether it positively enhances the effectiveness of lifestyle interventions. In order to define the effectiveness of intervention strategies, accurate measurement of physical activity is paramount for correct interpretation of study results. Several instruments exist to estimate physical activity levels, such as questionnaires and body-fixed activity monitors. When deciding which activity monitor to use in research and daily practice, popularity of a device is not necessarily the best option as it may not imply usability. Moreover, whether activity monitors can truly reflect the level of physical activity and sedentary behavior is still a subject of discussion.
The effectiveness of a multidisciplinary lifestyle program in increasing physical activity levels was evaluated in a study by Brenda Berendsen as part of her PhD thesis. The intervention was offered to 30 family practices across the Netherlands to more than 400 people by a team of nurses, physiotherapists and dieticians. In her PhD thesis defense, Brenda Berendsen presented distinct differences between activity monitors that were used in this study, these included the accuracy and ease of use. Three activity monitors were investigated: the CAM (forerunner of MOX, Maastricht Instruments), ActiGraphGT3X and ActivPal3. Results revealed that the differences in sitting, standing and time in motion was best represented by two monitors (CAM and ActivPAL3) that were worn on the thigh. Feedback from questionnaires on the CAM, ActiGraphGT3X and ActivPAL3 demonstrated that ActiGraphGT3X (46 x 33 x 15 mm; 19 g), worn around the waist, was very comfortable to wear. Participants found the CAM, which was the largest monitor (63 x 45 x 18 mm; 100 g), the most physically apparent while performing daily activities. With that consideration, Maastricht Instruments developed the MOX, a smaller monitor that is more compact and less obtrusive than the CAM.
Furthermore, Brenda Berendsen's dissertation described the process and effectiveness of an intervention to encourage exercise and healthy diet in overweight people. In addition, the study showed that an intervention of a multidisciplinary lifestyle program was effective in increasing physical activity levels. However, an adequate amount of delivered therapy hours was required to benefit from the physical activity program.
Brenda Berendsen, PhD
Open University Heerlen, Department of Psychology and Educational Sciences
Brenda Berendsen defended her thesis "Measurement and promotion of physical activity: Evaluation of activity monitors and a multidisciplinary lifestyle intervention in primary care" on June 24, 2016 at 14.00 at the University of Maastricht. Download the article here.
Using accelerometry sensors to determine the amount of arm activity in children with Duchenne Muscular Dystrophy and with Mitochondrial Disease
On December 5th, Arjen Bergsma defended his dissertation titled: “The upper limb in neuromuscular disorders - From basic function to daily life performance”. [1] Our arms are important in carrying out daily activities. A muscular disease can limit the arm function, so that people are no longer able to carry out their daily activities in the way they want. Arjen and his colleagues studied the problems and limitations of people with different types of muscle diseases in daily life, and they used several instruments to measure this. While several instruments are available to study basic function and people’s capacity to perform activities, little is known about performance in daily life. In previous studies, only the capacity of people to do certain activities has been evaluated in laboratory settings. It is, however, very well possible that people perform different in their daily life compared to a situation where they are observed in a laboratory setting. The use of accelerometers has been proposed to get insight in how active people use the arms during the day. In Nijmegen, MOX accelerometers were used to evaluate the feasibility of determining the amount of arm activity in children with Duchenne Muscular Dystrophy and with Mitochondrial Disease [2] during the day. In those studies, participants wore MOX sensors at the upper leg, upper arm, lower arm and chest during a few days. The average amount of counts per hour and the maximal intensity were calculated. The feasibility of using the sensors to get insight in daily life performance was demonstrated. The use of accelerometers is considered to be useful to evaluate the effect of training interventions and to evaluate how effective assistive devices like arm supports are being used in daily life. Information about the amount of arm activity may also be useful feedback for patients themselves, to get insight in how active they are with the arms during the day. In current studies, we used a research oriented user interface for the MOX sensors. For clinical implementation, a more user friendly interface is recommended.
Author: Dr. Ir. Arjen Bergsma
[1] Bergsma, A. The upper limb in neuromuscular disorders - From basic function to daily life performance, PhD thesis, Radboudumc Nijmegen, 2016
[2] Koene, S. et al., Domains of daily physical activity in children with mitochondrial disease: a 3D accelerometery approach, Journal of Inherited Metabolic Disease, accepted
This research is carried out as part of the McArm project. http://mcarm.eu
Continued arm activity monitoring developments are carried out in the Symbionics project.
