ARPEGE: Assessment of Frailty at Home

2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013)

ARPEGE: Assessment of Frailty at Home Rana Jaber, Aly Chkeir, David Hewson, Jacques Duchêne Institut Charles Delaunay, UMR CNRS 6279 Université de technologie de Troyes Troyes - France (rana.jaber, aly.chkeir, david.hewson, jacques.duchene)@utt.fr

One of the main objectives of the ARPEGE project is to provide a technological pack, including all the devices needed to estimate the Fried’s criteria, which could be used by natural or professional caregivers, or even by the elderly themselves at their home as a form of coaching. In addition the pack produces a score of balance quality, which is of particular importance with respect to risk of falls. Data collected from the ARPEGE pack must be reliable as measurements are mostly performed at home without a rigorous protocol. Therefore, the measurement devices must be robust with respect to the environmental conditions, especially the various home configurations, and requiring no specific skills for their use.

Abstract—The ARPEGE project proposes a set of technological tools to assess frailty of elderly in their usual environment, typically their home, with reference to Fried’s scale of physical frailty. It consists of a set of measurement devices wirelessly connected to a tablet PC which allows easy manipulation by social caregivers and the production of reports either at the end of the investigation, or later by consultation of the investigation history. The whole frailty evaluation takes a maximum of eight minutes to perform. Keywords—Frailty; Elderly; Objective evaluation

I.

INTRODUCTION

Living at home is nowadays more and more accepted, even demanded by the elderly in most European countries. On one hand this community dwelling situation presents a number of benefits for the elderly, especially living in a familiar environment, maintaining their social links, and carrying on their daily life activities. On the other hand such a population is subject to increasingly stressful situations (decrease in physical capacity, occurrence of pathologies, falls, break-up of social links, financial income reduction etc.) [1]. In addition their capability to react to those stressing events is reduced. These stressful conditions may induce a risk of frailty, hence a possible decline towards dependence if this frailty state is not detected early enough.

II.

The ARPEGE pack has to be used in a non-controlled environment for frailty detection, and potentially include follow-up and/or coaching at home. It seemed relevant, therefore, to use devices that were commercially available and often encountered at home, or at least familiar in the home environment. The idea was then to supplement these devices with additional functionalities allowing the production of the desired information. Most of the devices (except for walking speed) have been described in details in previous publications, so that their description will be limited to a short paragraph in the following sections. The main interest of the ARPEGE pack is to group together all measurement devices around a central device, a tablet PC with a user-friendly interface. The purpose is to make the use of the devices as easy as possible, with the production of the results immediately interpretable.

The frailty concept has considerably evolved in recent last years, even though there is still no consensus on its definition. However, several scales or models have been published in the last decade. The model of Rockwood and Mitnitski [2] is probably the most comprehensive (70 items), hence the most difficult to apply. Studenski et al [3] proposed a questionnaire of 39 items, covering items for physical capabilities as well as more subjective items like emotional or health state as perceived by the elderly themselves. The model of Strawbridge et al [4] addresses the frailty issue through four frailty dimensions: physical, nutritional, cognitive and sensory. Fried et al [5] addressed only physical frailty using five criteria: weight loss, exhaustion, physical activity, walk time, and grip strength. When the aim is to detect a frail or pre-frail state, at least three of Fried’s criteria can be calculated either objectively (walk time, grip strength) or at least partially (weight loss). If a follow-up is envisaged for a long period of time, weight loss and physical activity assessment can also be measured by objective devices.

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THE ARPEGE PACKAGE

A. Weight loss and balance quality Weight loss can be quantified using a standard bathroom scale (Balance Quality Tester: BQT) with communication capabilities. In the ARPEGE project, the raw signals provided by the scale sensors are processed in order to yield parameters that are relevant for balance quality scoring [6]. The BQT device (Fig. 1) is very easy to use: an IR sensor detects the presence of the subject and starts the calibration process, then displays “0.0”. The subject steps onto the scale and waits for the weight to be displayed (10 s), then steps off the scale, which sends its recordings to a remote receiver by Bluetooth (typically a tablet PC for the ARPEGE pack).

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signal provided by the sensor by Bluetooth. Dedicated software (still under development) will produce a global parameter that, based on preliminary results, should be highly correlated with walking speed estimated using standard clinical tests.

Fig. 1. Modified Bathroom scale.

B. Grip strength Many devices can provide a measure of grip strength, including the tools commonly considered as references, the Jamar® (Sammons & Preston, Bolingbrook, IL, USA) and the Vigorimeter® (Martin Medizintechnik, Tuttlingen, Germany) [7]. In order to overcome some limitations of these devices, such as the absence of remote communication or limited user-friendliness, an innovative device, called the “Grip-ball”, was developed [8] (Fig. 2). Among others, an interesting characteristic of the Grip-ball is that it can be inflated at different initial pressures, leading to stiffness that varies as a function of the initial pressure. A hybrid version prior to the availability of the final industrial product was developed that was partway between a Grip-ball and a Vigorimeter, with the manometer of the Vigorimeter replaced by the electronics of the Grip-ball

Fig. 3. Doppler sensor and associated electronics

D. Physical activity level Many attempts have been made to assess the physical activity level of a person during the day. Most devices rely on inertial sensors that are either embedded in custom made systems or already present in commercial devices such as mobile phones. Although these devices are well suited to longitudinal use and coaching, they are poorly adapted for frailty detection as they do not provide an instantaneous value of activity. A mobile phone has been included in an extended version of the ARPEGE pack dedicated to longitudinal assessment of frailty at home. Therefore, for frailty detection purposes, physical activity level is evaluated by questionnaire, with a modified single-question version of that used in the SHARE project [11], in which the person reports the frequency at which they perform activities such as shopping, gardening, taking a walk, etc. E. Exhaustion The double-item questionnaire used by Fried et al is based on a depression scale [5]. Fried’s questionnaire, which was translated from English to French, consists of two questions, one related to the feeling that everything requires an effort, the other related to the fact that the person could not get going.

Fig. 2. The Grip-ball and the hybrid device.

C. Walking speed This criterion is highly relevant for frailty assessment. It is commonly related to risk of fall and frequently used as part of a standardized geriatric evaluation [9, 10]. In clinical practice, the most popular way of measuring walking speed is to time the subject walking over a known distance (e.g. 15 feet for Fried [5]). However that kind of measurement (the time spent to cover a given distance) is not applicable at home, since the available distances are usually very small and not easily measurable. Therefore, there was a need for a device that could measure walking speed (instead of walking time) in an instantaneous manner, irrespective of the available distance. The device (Fig. 3) is based on the Doppler principle and makes use of a commercial Doppler sensor (X-Band Doppler Motion Detector MDU 1130, Microwave Solutions Ltd., Marlowes, UK). We designed the electronics in order to pre-process and transmit the

F. Human machine interface Software was implemented in a standard tablet PC (ST Latitude Tablet, Dell Inc., Round Rock, Texas, USA). When the tablet is switched on, the user can either go to a new evaluation or consult previous ones. Each subject has a unique identification number that includes a verification code in order to avoid errors when entering the number. The ID is the only alphanumerical data the user has to enter through a simplified virtual keyboard, as all other data needed is through the touch screen by means of icons and cursors. After the anthropometric data of the subject has been entered using touch cursors, the five tests of the Fried criteria are proposed to the investigator who can choose the tests in any order. All interactions between the investigator

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and the tablet are made via icons, with results and scores displayed graphically in a user-friendly manner. Fig. 4 shows an example of result displayed from the weight loss and balance test.

Fig. 4. An illustration of a result display (here weight and balance test).

When all tests have been completed (with the possibility for the subject to refuse one or more of them), a global synthesis of all results is displayed on the screen (Fig. 5), along with an estimation of Fried’s test result (not frail, prefrail, frail).

Fig. 6. Example of a report produced by the ARPEGE pack.

The second step is still in progress, with the aim being to test the usability of such the ARPEGE pack in real conditions at the homes of a cohort of 150 elderly visited by six investigators. A single one-hour training session was organized with the investigators who did not request any further training. None of the investigators made use of the user manual specifically designed for them.

Fig. 5. Synthetic presentation of the results.

Results are then stored in the folder corresponding to the person tested and/or transmitted to a remote server. The investigator has two possibilities. They can either consult the list of the evaluations that have already been performed. This gives access to a comprehensive report that can be displayed on the screen and/or saved on a USB key in a PDF format (Fig. 6). The investigator can also choose to transfer the results, which is performed by switching the tablet on when a 3G key inserted, something that automatically starts the transfer program to send all acquired data towards a remote server currently located at the university. This step requires no action from the user. III.

One important issue is the time spent specifically for the frailty evaluation, given that that task was performed in addition to the investigator’s usual tasks. The average time needed for the frailty evaluation has been estimated at around eight minutes, which is very short compared to the time spent for the other tasks (around 90 min, excluding the travel time for the investigator). The time taken to perform the test is automatically collected during the experiment. IV.

CONCLUSION

The ARPEGE pack was designed as a simple and userfriendly way for non-medical professionals to assess frailty in the elderly in their usual environment. A first experiment of 150 subjects has been started in order to test the acceptability and usability of such a technological pack. A second trial designed to explore the possibility for such a technology to be used by other professionals such as general practitioners or geriatricians in their office is also planned.

RESULTS

The ARPEGE pack was initially tested by social caregivers, who interview elderly people returning home after hospitalization. The human machine interface was developed via co-conception within the scope of the ActivAgeing Living Lab, meaning that very few modifications were required by those users.

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ACKNOWLEDGMENT This work was supported by the Champagne-Ardenne Regional Council (CRCA), the European Regional Development Fund under the Collaborative Research Program, and the Regional North-East Pension Fund (ARPEGE Project).

[10]

We would like to thank warmly the technical team of our laboratory for their major contribution to hardware and software developments.

[11]

REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

L. P. Fried, E. C. Hadley, J. D. Walston, A. B. Newman, J. M. Guralnik, S. Studenski, et al., "From Bedside to Bench: Research Agenda for Frailty," Sci. Aging Knowl. Environ., vol. 2005, pp. pe24-, August 3, 2005 2005. K. Rockwood and A. Mitnitski, "Frailty Defined by Deficit Accumulation and Geriatric Medicine Defined by Frailty," Clinics in Geriatric Medicine, vol. 27, pp. 17-26, 2011. S. Studenski, R. P. Hayes, R. Q. Leibowitz, R. Bode, L. Lavery, J. Walston, et al., "Clinical Global Impression of Change in Physical Frailty: Development of a Measure Based on Clinical Judgment," Journal of the American Geriatrics Society, vol. 52, pp. 1560-1566, 2004. W. J. Strawbridge, S. J. Shema, J. L. Balfour, H. R. Higby, and G. A. Kaplan, "Antecedents of frailty over three decades in an older cohort," Journals of Gerontology - Series B Psychological Sciences and Social Sciences, vol. 53, pp. S9-S16, 1998. L. P. Fried, C. M. Tangen, J. Walston, A. B. Newman, C. Hirsch, J. Gottdiener, et al., "Frailty in Older Adults: Evidence for a Phenotype," J Gerontol A Biol Sci Med Sci, vol. 56, pp. M146157, March 1, 2001 2001. J. Duchêne and D. J. Hewson, "Using a modified bathroom scale for long-term balance quality assessment: relevance, usability and acceptability," Journal of Telemedicine and Telecare, vol. 17, pp. 421-26, 2011. J. Desrosiers, R. Hebert, G. Bravo, and E. Dutil, "Comparison of the Jamar dynamometer and the Martin vigorimeter for grip strength measurements in a healthy elderly population," Scand J Rehabil Med, vol. 27, pp. 137-43, Sep 1995. R. Jaber, D. J. Hewson, and J. Duchêne, "Design and validation of the Grip-ball for measurement of hand grip strength," Medical Engineering and Physics, vol. 34, pp. 1356-1361, 2012. M. Montero-Odasso, M. Schapira, E. R. Soriano, M. Varela, R. Kaplan, L. A. Camera, et al., "Gait Velocity as a Single Predictor of Adverse Events in Healthy Seniors Aged 75 Years and Older," J

417

Gerontol A Biol Sci Med Sci vol. 60, pp. 13041309, 2005. G. Abellan van Kan, Y. Rolland, S. Andrieu, J. Bauer, O. Beauchet, M. Bonnefoy, et al., "Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force," J Nutr Health Aging, vol. 13, pp. 881-9, Dec 2009. M. C. Aichberger, M. A. Busch, F. M. Reischies, A. Ströhle, A. Heinz, and M. A. Rapp, "Effect of Physical Inactivity on Cognitive Performance after 2.5 Years of Follow-Up - Longitudinal Results from the Survey of Health, Ageing, and Retirement (SHARE)," GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, vol. 23, pp. 7-15, 2010.