Research
SCIENTIFIC PAPERS
Our product and our line of research, are supported by an extensive scientific literature, in this section are contained some of the papers that validate the use of smart wearables in the medical field for the prevention and management of neurodegenerative diseases.
Disability status and quality of life in multiple sclerosis: nonlinearity of the Expanded Disability Status Scale (EDSS). Health Qual Life Outcomes 2010;8:55.
Twork S, Wiesmeth S, Spindler M, et al.
Progression in disability as measured by increase in the Expanded Disability Status Scale (EDSS) is commonly used as outcome variable in clinical trials concerning multiple sclerosis (MS). In this study, we addressed the question, whether there is a linear relationship between disability status and health related quality of life (HRQOL) in MS.
Smart watch, smarter EDSS: Improving disability assessment in multiple sclerosis clinical practice. J Neurol Sci. 2017 Dec 15;383:166-168. doi: 10.1016/j.jns.2017.10.043. Epub 2017 Oct 27.
Dalla-Costa G, Radaelli M, Maida S, Sangalli F, Colombo B, Moiola L, Comi G, Martinelli V.
Patients’ walking ability is critical for assessing the EDSS, the disability scale commonly used in MS clinical practice. Such assessment is usually based on patients’ estimates or on the measures the neurologists observe during periodic visits. quality of life (HRQOL) in MS.
Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study. J Med Internet Res. 2019 Aug 30;21(8):e14863.
Midaglia L, Mulero P, Montalban X, Graves J, Hauser SL, Julian L, Baker M, Schadrack J, Gossens C, Scotland A, Lipsmeier F, van Beek J, Bernasconi C, Belachew S, Lindemann M.
Current clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits.
Classification of wearable computing: A survey of electronic assistive technology and future design. In Proceedings of the 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), Kolkata, India, 23–25 September 2016; pp. 22–27.
Chatterjee, A.; Aceves, A.; Dungca, R.; Flores, H.; Giddens, K.
In the past decade there have been significant advancements in computer technology that have reduced the hardware form factor as well as increased energy efficient computing. Using network protocols for near field communication such as Body Area Networks (BANs), smaller and lighter computing units with attached sensors have transformed into wearable devices.
Gait and balance impairment in early multiple sclerosis in the absence of clinical disability. Mult Scler (2006) 12:620–8. doi:10.1177/1352458506070658
Martin CL, Phillips BA, Kilpatrick TJ, Butzkueven H, Tubridy N, Mcdonald E, et al.
This study evaluated the gait and balance performance of two clinically distinct groups of recently diagnosed and minimally impaired multiple sclerosis (MS) patients (Expanded Disability Status Scale range 0-2.5), compared to control subjects.
Gait and balance deterioration over a 12-month period in multiple sclerosis patients with EDSS scores
Galea MP, Cofre Lizama LE, Butzkueven H, Kilpatrick TJ.
It is not currently known whether gait and balance measures are responsive to deterioration of motor function in multiple sclerosis (MS) patients with low EDSS scores (≤3.0). The aim of this study was to quantify MS-related gait and balance deterioration over a 12-month period.
“Objective physical activity measurement in people with multiple sclerosis: a review of the literature” Disability and Rehabilitation: Assistive Technology, vol. 13, no. 2, pp. 124–131, 2018.
B. Casey, S. Coote, and A. Donnelly,
The purpose of this study is to identify the objective physical activity (PA) measurement tools and outputs that are used within Multiple Sclerosis (MS) literature.
Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis. Translational Clin 2016;2.
Balto JM, Kinnett-Hopkins DL, MOtl RW.
There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients.
Continuous daily assessment of multiple sclerosis disability using remote step count monitoring. J Neurol 2017;264:316–326.
Block VJ, Lizee A, Crabtree-Hartman E, et al.
Disability measures in multiple sclerosis (MS) rely heavily on ambulatory function, and current metrics fail to capture potentially important variability in walking behavior. We sought to determine whether remote step count monitoring using a consumer-friendly accelerometer (Fitbit Flex) can enhance MS disability assessment.
Predicting habitual walking performance in multiple sclerosis: relevance of capacity and self-report measures. Mult Scler 2010;16:618–626.
Gijbels D, Alders G, Van Hoof E, et al.
The objective was to establish the extent to which physical functioning capacity and self-report measures are able to predict the habitual walking performance in ambulatory persons with multiple sclerosis.
Quantitative assessment of multiple sclerosis using inertial sensors and the TUG test. Conf Proc IEEE Eng Med Biol Soc2014; 2014: 2977–2980.22.
Greene BR, Healy M, Rutledge S, et al.
Multiple sclerosis (MS) is a progressive neurological disorder affecting between 2 and 2.5 million people globally. Tests of mobility form part of clinical assessments of MS. Quantitative assessment of mobility using inertial sensors has the potential to provide objective, longitudinal monitoring of disease progression in patients with MS.
Association of Continuous Assessment of Step Count by Remote Monitoring With Disability Progression Among Adults With Multiple Sclerosis. JAMA Netw Open. 2019 Mar 1;2(3):e190570.
Block VJ, Bove R, Zhao C, Garcha P, Graves J, Romeo AR, Green AJ, Allen DD, Hollenbach JA, Olgin JE, Marcus GM, Pletcher MJ, Cree BAC, Gelfand JM.
Disability measures in multiple sclerosis (MS) fail to capture potentially important variability in walking behavior. More sensitive and ecologically valid outcome measures are needed to advance MS research.
Wearable technology reveals gait compensations, unstable walking patterns and fatigue in people with multiple sclerosis. Physiol Meas. 2018 Jul 16;39(7):075004
Psarakis M, Greene DA, Cole MH, Lord SR, Hoang P, Brodie M.
People with multiple sclerosis (PwMS) often experience a decline in gait performance, which can compromise their independence and increase falls. Ankle joint contractures in PwMS are common and often result in compensatory gait patterns to accommodate reduced ankle range of motion (ROM).
Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis. Front Neurol. 2018;8:708. Published 2018 Feb 2.
Shanahan CJ, Boonstra FMC, Cofré Lizama LE, et al.
Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease.
Disability status and quality of life in multiple sclerosis: nonlinearity of the Expanded Disability Status Scale (EDSS). Health Qual Life Outcomes 2010;8:55.
Twork S, Wiesmeth S, Spindler M, et al.
Progression in disability as measured by increase in the Expanded Disability Status Scale (EDSS) is commonly used as outcome variable in clinical trials concerning multiple sclerosis (MS). In this study, we addressed the question, whether there is a linear relationship between disability status and health related quality of life (HRQOL) in MS.
Smart watch, smarter EDSS: Improving disability assessment in multiple sclerosis clinical practice. J Neurol Sci. 2017 Dec 15;383:166-168. doi: 10.1016/j.jns.2017.10.043. Epub 2017 Oct 27.
Dalla-Costa G, Radaelli M, Maida S, Sangalli F, Colombo B, Moiola L, Comi G, Martinelli V.
Patients’ walking ability is critical for assessing the EDSS, the disability scale commonly used in MS clinical practice. Such assessment is usually based on patients’ estimates or on the measures the neurologists observe during periodic visits. quality of life (HRQOL) in MS.
Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study. J Med Internet Res. 2019 Aug 30;21(8):e14863.
Midaglia L, Mulero P, Montalban X, Graves J, Hauser SL, Julian L, Baker M, Schadrack J, Gossens C, Scotland A, Lipsmeier F, van Beek J, Bernasconi C, Belachew S, Lindemann M.
Current clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits.
Classification of wearable computing: A survey of electronic assistive technology and future design. In Proceedings of the 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), Kolkata, India, 23–25 September 2016; pp. 22–27.
Chatterjee, A.; Aceves, A.; Dungca, R.; Flores, H.; Giddens, K.
In the past decade there have been significant advancements in computer technology that have reduced the hardware form factor as well as increased energy efficient computing. Using network protocols for near field communication such as Body Area Networks (BANs), smaller and lighter computing units with attached sensors have transformed into wearable devices.
Gait and balance impairment in early multiple sclerosis in the absence of clinical disability. Mult Scler (2006) 12:620–8. doi:10.1177/1352458506070658
Martin CL, Phillips BA, Kilpatrick TJ, Butzkueven H, Tubridy N, Mcdonald E, et al.
This study evaluated the gait and balance performance of two clinically distinct groups of recently diagnosed and minimally impaired multiple sclerosis (MS) patients (Expanded Disability Status Scale range 0-2.5), compared to control subjects.
Gait and balance deterioration over a 12-month period in multiple sclerosis patients with EDSS scores
Galea MP, Cofre Lizama LE, Butzkueven H, Kilpatrick TJ.
It is not currently known whether gait and balance measures are responsive to deterioration of motor function in multiple sclerosis (MS) patients with low EDSS scores (≤3.0). The aim of this study was to quantify MS-related gait and balance deterioration over a 12-month period.
“Objective physical activity measurement in people with multiple sclerosis: a review of the literature” Disability and Rehabilitation: Assistive Technology, vol. 13, no. 2, pp. 124–131, 2018.
B. Casey, S. Coote, and A. Donnelly,
The purpose of this study is to identify the objective physical activity (PA) measurement tools and outputs that are used within Multiple Sclerosis (MS) literature.
Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis. Translational Clin 2016;2.
Balto JM, Kinnett-Hopkins DL, MOtl RW.
There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients.
Continuous daily assessment of multiple sclerosis disability using remote step count monitoring. J Neurol 2017;264:316–326.
Block VJ, Lizee A, Crabtree-Hartman E, et al.
Disability measures in multiple sclerosis (MS) rely heavily on ambulatory function, and current metrics fail to capture potentially important variability in walking behavior. We sought to determine whether remote step count monitoring using a consumer-friendly accelerometer (Fitbit Flex) can enhance MS disability assessment.
Predicting habitual walking performance in multiple sclerosis: relevance of capacity and self-report measures. Mult Scler 2010;16:618–626.
Gijbels D, Alders G, Van Hoof E, et al.
The objective was to establish the extent to which physical functioning capacity and self-report measures are able to predict the habitual walking performance in ambulatory persons with multiple sclerosis.
Quantitative assessment of multiple sclerosis using inertial sensors and the TUG test. Conf Proc IEEE Eng Med Biol Soc2014; 2014: 2977–2980.22.
Greene BR, Healy M, Rutledge S, et al.
Multiple sclerosis (MS) is a progressive neurological disorder affecting between 2 and 2.5 million people globally. Tests of mobility form part of clinical assessments of MS. Quantitative assessment of mobility using inertial sensors has the potential to provide objective, longitudinal monitoring of disease progression in patients with MS.
Association of Continuous Assessment of Step Count by Remote Monitoring With Disability Progression Among Adults With Multiple Sclerosis. JAMA Netw Open. 2019 Mar 1;2(3):e190570.
Block VJ, Bove R, Zhao C, Garcha P, Graves J, Romeo AR, Green AJ, Allen DD, Hollenbach JA, Olgin JE, Marcus GM, Pletcher MJ, Cree BAC, Gelfand JM.
Disability measures in multiple sclerosis (MS) fail to capture potentially important variability in walking behavior. More sensitive and ecologically valid outcome measures are needed to advance MS research.
Wearable technology reveals gait compensations, unstable walking patterns and fatigue in people with multiple sclerosis. Physiol Meas. 2018 Jul 16;39(7):075004
Psarakis M, Greene DA, Cole MH, Lord SR, Hoang P, Brodie M.
People with multiple sclerosis (PwMS) often experience a decline in gait performance, which can compromise their independence and increase falls. Ankle joint contractures in PwMS are common and often result in compensatory gait patterns to accommodate reduced ankle range of motion (ROM).
Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis. Front Neurol. 2018;8:708. Published 2018 Feb 2.
Shanahan CJ, Boonstra FMC, Cofré Lizama LE, et al.
Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease.