Wagner, Flo BPT, MSc; Basran, Jenny MD, BSc, FRCPC; Bello-Haas, Vanina Dal BScPT, MEd, PhD
Many Americans are living longer, and recent studies have reported that the majority of older adults wish to live as independently as possible in their own homes, for as long as possible.1,2 The United Nations Population Division projects that by the year 2050, 27% of the population of the United States will be older than 60 years, with 8% older than 80 years.3 This trend will impact health care costs as the baby boomers begin qualifying for Medicare in 2011, resulting in many of the costs being shifted to the public sector.4 An additional concern is the trend toward shorter lengths of stay in hospital following an acute illness or injury, with discharge home often occurring before full recovery of previous activity levels.5 As a result of these changes in health care delivery there will be an increased need to provide adequate care and supervision for older adults when they return to their homes.
For older adults living independently in the community there is often a need to find a balance between risk and safety. The risk of injury during activities of daily living is weighed against the desire to maintain independence. The older adult may become more prudent in his or her daily life to be safer, but living alone presents challenges that often cause concern for the individual and the family or caregiver. Personal alarms or various monitoring systems can provide an increased level of reassurance about the safety and security of the older adult at home.
Relevance to Physical Therapy
Technological monitoring of daily activities can not only detect a fall or an emergency situation but also provide clinicians with a method to detect changes that would suggest a decline in medical status or an increased risk of falling. The ability to detect and assess a problem with mobility or function while its effect is small may provide a window of opportunity for intervention before the problem becomes catastrophic.
In the past several years, advancements have been made in technology specifically developed for monitoring the movement and activity of older adults in their homes. This technology can provide family members or caregivers an opportunity to provide support and still allow independence. For example, these devices can offer increased safety by providing a mechanism that ensures older adults have access to assistance at home when required in an emergency. Monitoring technology can also provide ongoing evaluation of activities of daily living to provide anincreased reassurance that the older adult is managing safely.
The purpose of this article is to provide a narrative review of current monitoring technology appropriate for older adults' home use. The focus of the review is on technology that allows unobtrusive monitoring but does not require detailed attention of the wearer, which would ensure ease of use for older adults.
A number of online databases and search engines were examined by the authors for this review, including PubMed, EBSCO, and Google Scholar. The Institute of Electrical and Electronics Engineers (IEEE) Xplore digital library was searched for additional conference proceedings. Bibliographies of relevant papers and abstracts were screened for additional resources. The key search words and phrases used were “aging in place,” “monitoring elderly,” “falls detection,” “smart homes,” “wearable technology,” and “wearable devices.” Articles written in English and published between 2001 and 2010 were included.
In an effort to limit the scope of the review, we did not include assistive technology key words, such as “mobility aids,” “daily living aids,” or “accommodation adaptations,” although these can also contribute to facilitating independence.
In total 162 papers and abstracts that examined developments in monitoring technology or the use of monitoring technology for older adults were examined by the authors. Papers were not included in this review if the device presented had not reached the stage of clinical testing, or if they were duplicating information. Forty-five papers were included in this paper to provide a comprehensive review of the current technology. This review was not intended to provide an exhaustive list of all the initiatives in development or available worldwide, but rather a comprehensive discussion of the current technology.
For the purposes of our narrative review, we categorized the results into the following: personal alarm devices; falls detection devices; activity monitoring devices; and wearable technology.
Personal Alarm Devices
Personal user-based alarms have been available for many years.6 These alarms, which are usually worn as a pendant or on the wrist, are activated by the older adult pressing a button on the unit in the event of a fall or other emergency situation. The activated alarm notifies a monitoring station, which in turn activates a predetermined response. These devices are widely available and offer a level of security for the older adult by providing an easy method of calling for assistance when required in an emergency situation. A reported drawback of this emergency service is that it is only effective if the older adult is actually wearing the device. Reasons for not wearing the alarm include forgetting to put it on, worry about damage, discomfort of wearing the device, or thinking that it will not be needed.6 In addition, the older adult must be able to recognize the emergency and have the physical and mental capacity to press the alarm.7
Falls Detection Devices
A number of monitoring devices are primarily focused on detection of falls. These devices can be described in 3 categories: (1) video-based monitoring of real-time movement, so the actual fall is observed; (2) acoustic frequency or floor vibration-based monitoring, where falls are detected by analyzing the frequency components of sounds or vibration caused by the impact of a fall; and (3) wearable sensor-based monitoring, in which falls are detected by sensors attached to the subject. Some of these devices incorporate an alarm system, whereby once a fall is detected an alarm is sent to caregivers. The intent of these monitoring devices, which do not require the active involvement of the older adult, is to minimize the time between a fall and the arrival of a caregiver or medical attention.8,9
An example of a video surveillance system, which is in development, uses a 3D wall-mounted camera to track the head of the person.10 The system is intended to distinguish falls from normal activity, but the pilot testing reported only detecting falls 2 of 3 times. In particular, detection of a fall from a sitting position was unreliable because the head velocity was too low.10 The advantage of the video monitoring system is that it does not rely on the older adult remembering to wear or activate a detector such as a call button, while a drawback is that the individual may experience a feeling of “being watched.”11
A floor vibration-based fall detector is also completely passive and unobtrusive to the individual. This type of device detects falls by monitoring the vibration patterns in the floor. They are currently being tested and evaluated to ensure that they can detect the difference between a fall and activities such as walking or an object falling on the floor.11 On the basis of initial testing, the fall detection range of a single sensor is 15 to 20 ft, or about the size of 1 room, meaning each room would require at least 1 sensor. If a fall is detected, an alert can be generated utilizing a cell phone or radio pager to a caregiver or prearranged response center.11
The acoustic fall detection system relies on detectors placed throughout the residence of an older adult. The analysis of sounds collected from these wall-mounted sensors will recognize a fall event.9 A major challenge of the acoustic system is false alarms. The investigator has reported that the integration of a motion detector into this type of system is intended in future development to assist in analysis and fall detection. For example, an integrated motion detector would cancel the fall alert ifmovement is sensed after the event. This pilot project collected limited data based on 23 falls. Falls were performed by a stunt actor who had been instructed to simulate a variety of different falls such as forward, backward, and from a chair.9 Future research on this type of system will examine use with various floor surfaces, such as carpet and hard wood, people of different size, and weight, and add more sound sources, such as radio and television.9
Activity Monitoring Devices
There is a wide array of devices intended to provide passive, unobtrusive monitoring of activity. Door alarms are particularly helpful for those who may wander7 and can activate an alarm once triggered. Pressure mats can be positioned in the bed or chair to identify a change in pressure if the individual gets up. The pressure mats can also be linked to the lighting in the room, illuminating the room when the person rises.7 An “intelligent bed care system” is being tested in Japan,12 which employs sensors under the bedsheets to detect both body movement and leaking of fluids such as bleeding or incontinence. This system can trigger an alert if needed as well as provide a record of body movement to monitor sleep, rest periods and restlessness over time. These devices were designed for hospital or long-term care facilities, although some sensor devices have been incorporated into home monitoring as well.
Sensors placed in various locations in the home such as the refrigerator door, stove, or dresser drawers can help to monitor activity levels on a day-to-day basis and provide safety checks for hazards such as fire or gas leaks.13 QuietCare (Intel-GE Care Innovations, LLC, Roseville, California) is a commercially available example of a remote health monitoring and emergency alert system available in the United States. It provides 5 small, wireless motion sensors placed in various locations in the home. The system “learns” the normal behavior of an individual and the QuietCare software analyzes data, looking for trends, and changes in routine. A report is generated daily, which can be viewed by family or care- givers. Examples of questions that can be answered with this type of monitoring include: Did the resident get out of bed? Did they visit the bathroom and exit within 60 minutes? Did they visit the area where medication is stored? Was there activity in the meal preparation area? Has overall activity changed or decreased? An alert will notify the system monitors in the event of detected emergency situations. In addition, the resident is provided with a personal emergency panic button.14
When the entire residence incorporates this activity- monitoring technology, it is referred to as a Smart Home.15 A systematic review of Smart Home applications16 reported 21 smart home projects throughout the world utilizing a variety of different technologies. For example, PROSAFE, a mulltisensor home monitoring system in France, has been developed and piloted within a seniors' institution.17 This system monitors time in bed, in-bed restlessness, getting up, and frequency of going to the toilet. Analyses of these types of data can identify trends in behavior and alert caregivers about changes.
There are also examples of smart homes being developed in the United States. The Georgia Institute of Technology has developed the Aware Home Research Initiative.18 This 3-story, 5040-square-foot home functions as a living laboratory for interdisciplinary design, development, and evaluation. It is “devoted to the multi- disciplinary exploration of emerging technologies and services for the home.”18 The Aware Home even includes a system of tracking and sensing technologies to help find frequently lost objects such as wallets, glasses, and keys. Each item is fit with a small radio-frequency tag and the resident can initiate a search by identifying the object on a touch screen. The system then guides the user to the lost object using audio cues.13
TigerPlace is an independent retirement facility developed by the University of Missouri-Columbia in partnership with Americare Corporation.19,20 It is not only a senior living facility but also an interdisciplinary educational and research venue. The facility was developed on the basis of the principle of “aging in place” and offers a variety of services that will enable the residents to remain in their home in the retirement facility for as long as pos- sible.20 The in-home monitoring system detects motion, has stove temperature sensors, and sensors on cabinet doors. The bed sensors detect presence, respiration, pulse, and movement in the bed. The system is designed to detect “alert” situations such as a fall, a stove left on, or a sudden change in physiological sensor data that may indicate a medical event. It can also identify a change in daily activity patterns that may indicate abnormalities or deteriorating health.19,20
Although there have been many new developments in this area, a recent Cochrane Review15 found no studies testing the effectiveness of smart home technology. They reported that it is not known what effects this smart technology has on supporting the older adult in their home. Demiris and Hensel16 reported that none of the studies they reviewed presented any evidence of the effects of smart home technology on health outcomes including injury detection and intervention. It has been suggested that large randomized controlled studies will need to be undertaken once this technology is more widespread.16,21
Wearable technology—wearable body area networks or wireless sensor networks—are mobile electronic devices that can be worn or unobtrusively embedded in clothing or an accessory. Recent advancements in this technology have produced a variety of applications related to the older adult population, although most are not available yet commercially. Zheng et al8 describes an automatic fall detector composed of a waist-worn 3-axis accelerometer, which uses a 2-stage fall detection algorithm. The first stage is the detection of a sudden impact and the second stage is the orientation of the wearer to determine whether there has been a significant change in body orientation compared to before the impact.8 If a fall is detected, the device can locate the wearer by using global positioning system and send and alarm to a family member or caregiver.
MEMSWear (Microelectromechanical Systems) is a wearable shirt that can detect falls through the use of gyroscopes and accelerometers.5,22 It can immediately transmit an alarm to a remote mobile device through the wearer's personal digital assistant (PDA) phone using BlueTooth (Bluetooth SIG, Inc, Kirkland, Washington).5 Further development of this PDA-type monitor includes the monitoring of blood pressure and heart rhythm using a one-lead electrocardiogram (ECG). This MEMSWear II device uses dynamic sensors (accelerometer and gyroscope) to monitor motion. Development will incorporate a fall prediction model that processes physical gait motion and physiological information to predict a fall. Once the fall prediction model reveals that a fall is imminent, it will activate the deployment of an air-inflatable hip-protection device, located in the lap of the shirt, to minimize injury, should a fall occur.23
AMON (Advanced care and alert portable telemedical MONitor)24 is a wrist-worn medical monitoring and alert system designed for people with high-risk cardiac or respiratory problems. It collects and evaluates vital signs such as heart rate, heart rhythm via ECG, temperature, blood pressure, and blood oxygen saturation.
This wrist-worn device is intended for monitoring these individuals outside a hospital setting, enabling a quicker return to usual activities. The device is easy to don without assistance and is to be worn on a daily basis. It has a 2-axis accelerometer capable of detecting the level of user activity and correlating it with vital signs. A GSM (global system for mobile communication) transceiver can exchange data with a medical center. Heart rate, skin temperature, oxygen saturation, and activity are monitored continuously, but blood pressure and one-lead ECG are only measured 3 times a day or on demand. Some inconsistency in the medical data that are collected has been reported.24,25 Although measurements of pulse and systolic blood pressure were considered reliable, body temperature could not be accurately established, measurements of blood oxygen saturation were not reliable, and the ECG readings provided poor results because of high levels of “noise,” or interference, in the signal. The device also requires specific positioning for the various readings. For example, for blood pressure measurement, the left arm (wearing the device) needs to be at the same level as the heart, positioned at, but not holding the shoulder, and for the ECG reading the individual must touch the right arm with the left hand while the device is in contact with the abdomen.24 This could be difficult for many older adults, especially those with memory, cognitive, visual, or physical impairments.
The “Smart Vest”25 is a wearable physiological monitoring system, which is built into a washable T-shirt. The system consists of a shirt with embedded sensors, a data acquisition and processing hardware device with embedded software worn on the waist, wireless transmission and a remote monitoring station. The Smart Vest monitors heart rhythm via ECG, oxygen saturation, body temperature, blood pressure, galvanic skin response, and heart rate. It has sensors placed at specific body locations and connected by wires, which are woven or stitched into the fabric. The oxygen saturation sensor is placed on the index finger or earlobe. The data acquisition hardware, connecting to the vest and worn around the waist, houses a battery and the electronics for processing and wireless transmission of the data. The developer reports that the Smart Vest prototypes have not been consistent in achieving medical accuracy on all measurements,25 especially blood pressure measurement during dynamic conditions such as walking.
Development of wearable technology has been undertaken by both the US Armed Forces and the National Aeronautics and Space Administration (NASA). The advancement of complex wearable physiological monitoring systems for use in combat uniforms and for astronauts may ultimately also have application in health care as well. An example is NASA's “LifeGuard” system for astronauts,26,27 which monitors heart rhythm via ECG, respiration rate, pulse oximetry, blood pressure, temperature and monitors activity via an accelerometer. The data are collected in a small wearable computer, which logs the physiological parameters and can perform rudimentary analysis of physiological status. The data can be transmitted wirelessly, via BlueTooth for further processing. The sensors are mostly external to the device, using traditional electrodes and a cuff-based blood pressure device making the donning and doffing of this system more complex.
Another example is the Georgia Tech “Smart Shirt,” funded by the US Department of Navy.28 This Smart Shirt, referred to as the “wearable motherboard” because it uses the “fabric as the computer,”28,29 is a flexible wearable monitoring device, which can transmit vital signs.
Suggested applications include monitoring of astronauts in space, firefighters, policemen, and soldiers who encounter major threats in their lines of duty.28 Potential medical applications of this wearable technology could also include improved clinical management of chronic medical conditions such as chronic obstructive pulmonary disease or Parkinson disease,30,31 conditions that are common in older adults. The ability to measure the physical activity of an individual with chronic obstructive pulmonary disease in their home, combined with heart rate, respiratory rate, and oxygen saturation could facilitate improved management of symptoms. In people with Parkinson disease, motor symptoms such as tremor, bradykinesia (slowness of movement), and rigidity (stiffness of movement) fluctuate during the day and vary in response to medication. A wearable device could assist in management of medication dosage or medication adjustments by providing an objective measure of symptoms over time, which is difficult to achieve with direct patient observation.30,31
Falls risk assessment is another application of wearable technology. It has been suggested that accelerometry offers an objective measurement of movement and can be used to develop a home-monitoring falls risk classification system.32
Marschollek et al32 described an accelerometry-based device to assess the falls risk (classified as low or high risk) of the older adult by analyzing data transmitted from the waist-worn tri-axial accelerometer. The device is intended to provide a simple, unsupervised method of assessing a persons' fall risk over extended periods of time by detection of subtle changes in movement or activity, which could signal an increased risk of falling for the older adult.
Classification (low or high risk) was compared to results of 3 commonly used clinical risk scores:
1. The Timed Up and Go (TUG),33 a test of general mobility,
2. The STRATIFY34 score, a test for mobility following stroke, and
3. The Barthel Index subscore of mobility.35
Testing of the device demonstrated that overall accuracy, compared to the 3 clinical reference scores, ranged from 65.5% to 89.1%, with sensitivity between 78.5% (STRATIFY score) and 99% (TUG) and specificity between 15.4% (TUG) and 60.4% (STRATIFY score).32 The authors suggest that more research is required to evaluate findings against actual fall rate per person over time.
Narayanan et al36 reported a single waist-mounted tri-axial accelerometer system that evaluated falls risk and functional deficits by monitoring a set of movement tasks referred to as a directed routine.36 This directed routine, performed unsupervised, included an Alternate Step Test, Timed Up and Go Test, and the Sit-to-Stand 5. The Alternate Step Test is performed by placing each foot onto then off a 19 cm high platform 4 times, alternating feet as quickly as possible. The Sit-to-Stand 5 is a 5-repetition sit-to-stand test. The movement data recorded by the accelerometer was transmitted by BlueTooth to a nearby laptop. Using data collected from 68 subjects, linear least-squares models were used to estimate fall risk and to identify deficits such as knee extensor weakness. These findings were compared to the physiological profile assessment (PPA),37 which had been performed first to establish a comparative measure. The PPA is a validated falls risk assessment tool measuring body sway, proprioception, knee extension strength, contrast sensitivity, and reaction time. It has demonstrated 75% to 79% accuracy in predicting participants with history of multiple falls from those without history of multiple falls.37
The model estimates provided good to fair correlations with falls risk (r = 0.76; P < 0.001) and knee extension strength (r = 0.65; P < 0.001) as determined by the PPA. Further development of this device includes attempting to improve performance by reducing model error and selecting alternate movements that would correlate with fall risk.36
This review describes several kinds of monitoring devices, many of which are in early stages of development and still require extensive testing regarding validity, reliability, acceptability, and utility. Many devices are not available yet commercially or are being used in limited settings such as in the TigerPlace smart home.
Several challenges still exist in the implementation of this technology. Many devices described in this review had limitations with reliability in measurement of physiological parameters as well as accurate algorithms for fall detection. Distinguishing a fall from normal activity is not always clear-cut, thus detection is not exact and can result in false alarms. False alarms could become a nuisance for the older adult and could quickly lead to disuse. Unforeseen malfunctions could also result in inaccurate information being transmitted because devices do not have mechanisms to monitor accuracy or overall system performance.38
Acceptability of monitoring devices by the older adult is another issue to consider. Any monitoring device needs to be unobtrusive, easy to use, easy to apply, and free of any social stigma.31 It has been reported that technology would be considered acceptable to older adults if it would allow them to remain in their own home.39,40 A recent study reports that emergency call systems as well as health and activity monitoring were rated as “most useful” by older adult participants interviewed, while videophones as “hardly useful.”41 It has also been reported that although this technology is viewed as favorable overall by older adults, many comments made indicated that technology is useful if it was used by “others” or “someone else who may need it.”40 This suggests a potential for discrepancy in older adults' perception of their need versus caregivers or family members' perceptions of needs.2,42 Acceptance of monitoring technology may be seen as acknowledgement of their frailty both to themselves and to others.42
Although concerns about privacy have been identified, it would seem that the perception of need for the technology may override these privacy concerns.42,43 However, a balance between the benefits of monitoring and the perceived intrusion of privacy is necessary.20 Another balance that must be struck is between the human and technical contribution to care.2 Although monitoring technology may assist in supporting independent living, it cannot replace human contact or support. Personal contact, touch, and respect for the individual receiving care are important.2,16,44
There are also issues regarding security of data being transmitted as well as determining and limiting who should have access to the data.16,38,45 It is important to ensure that the regulatory process provides adequate oversight and standards for systems that transmit data.38 Consent of the older adult may also present a concern, especially if there are any cognitive issues or if it is the concerned family that is implementing the system.
And finally, cost of implementation and cost effectiveness need to be determined.38 A 2008 review16 reported that none of the studies reviewed presented any evidence of the effects of smart home technology on health outcomes including injury detection and intervention. It has been suggested that large randomized controlled studies will need to be undertaken once this technology is more widespread.16,21
The area of unobtrusive monitoring and wearable technology holds great promise for the older adult, particularly for those who wish to remain in their home.31,45 As the baby boomers age, maintaining independence will be increasingly important and finding ways to support older adults in their homes increasingly necessary. Using technology to monitor and assess activity or detect if a fall or other emergency occurs has the potential to provide alternatives for ensuring that older adults are managing safely in their home environment. This in turn could positively affect both well-being and quality of life. More development is necessary to ensure that monitoring and detection is accurate and that reporting and response mechanisms are timely and effective. At present, there are only a few commercial services available that utilize wireless monitoring sensors and alarm systems but future development will likely produce many more.
Multidisciplinary approaches to development would be ideal to combine the technology with the clinical application and evaluation.45 Future research also needs to examine the validity, reliability, acceptability, and cost-effectiveness of device use in various settings, including the home setting. Technology is continuously changing, and advancing and new applications of technology may be of great benefit to help the older adult live safely in their home environment.
This narrative review summarizes some of the advancements that are being made in this changing field of technology. These devices are designed to provide unobtrusive monitoring of individuals, including older adults, without interfering with activity or requiring detailed attention of the wearer. To date, there has been little research on the reliability, validity, or the effectiveness of this technology on outcomes such as supporting older adults in their homes.15 However, this is an area of expanding development that holds much promise.31,45 In the future, this new technology may produce a variety of devices to offer community living older adults a level of increased security and safety in their homes.
2. McCreadie C. The acceptability of assistance technology to older people. Ageing soc. 2005;25(1):91–110.
5. Guo D, Xu L, Nyan M, Yap K, Tay F. MEMSWear-biomonitoring system for remote vital signs monitoring. J Franklin Inst. 2009;346(6):531.
6. De San Miguel K, Lewin G. Personal emergency alarms: what impact do they have on older people's lives? Australas J Ageing. 2008;27(2):103–105.
7. Miskelly FG. Assistive technology in elderly care. Age Ageing. 2001;30(6):455–458.
8. Zheng J, Zhang G, Wu T. Design of automatic fall detector for elderly based on triaxial accelerometer. Paper presented at: 3rd International Conference on Bioinformatics and Biomedical Engineering; June 11–13, 2009; Beijing, China.
9. Popescu M, Li Y, Skubic M, Rantz M. An acoustic fall detector system that uses sound height information to reduce the false alarm rate. Conf Proc IEEE Eng Med Biol Soc. 2008:4628–4631.
10. Rougier C, Meunier J, St-Arnaud A, Rousseau J. Monocular 3D head tracking to detect falls of elderly people. Conf Proc IEEE Eng Med Biol Soc. 2006;1:6384- 6387.
11. Alwan M, Ragendran RJ, Kell S, et al. A smart and passive floor-vibration based fall detector for elderly. Paper presented at: 2nd International Conference on Information and Communication Technologies; April 24–28, 2006; Damascus, Syria.
12. Yonqzawa Y, Miyamoto Y, Maki H, et al. A new intelligent bed care system for hospital and home patients. Biomed Instrum Tech. 2005;39(4):313–319.
13. Chan M, Esteve D, Escriba C, Campo E. A review of smart homes—present state and future challenges. Comput Methods Programs Biomed. 2008;91(1):55–81.
15. Martin S, Kelly G, Kernohan WG, McCreight B, Nugent C. Smart home technologies for health and social care support. Cochrane Database Syst Rev. 2008;(4):CD006412.
16. Demiris G, Hensel BK. Technologies for an aging society: a systematic review of “smart home” applications. Yearb Med Inform. 2008:33–40.
17. Chan M, Campo E, Esteve D. Assessment of activity of elderly people using a home monitoring system. Int J Rehabiltation Res. 2005;28(1):69–76.
19. Rantz M, Aud M, Alexander G, et al. TgerPlace: an innovative educational and research environment. In: Proceedings of AAAI Fall Symposia AI in Eldercare: New Solutions to Old Problems; November 7-9, 2008; Washington, DC.
20. Demiris G, Oliver DP, Dickey G, Skubic M, Rantz M. Findings from a participatory evaluation of a smart home application for older adults. Technol Health Care. 2008;16:111–118.
21. Brandt A, Samuelsson K, Toytari O, Salminen A. Activity and participation, quality of life and user satisfaction outcomes of environmental control systems and smart home technology: a systematic review. Disabil Rehabil Assist Technol. 2011;6(3):189–206. http://dx.doi.org/10.3109/17483107.2010.532286
23. Choon Po SN, Dagang G, Hapipi MCBM, et al. Overview of MEMSWear II— incorporating MEMS technology into smart shirt for geriatric care. J Phys: Conf Ser. 2006;34:1079–1085.
24. Anliker U, Ward JA, Lukowicz P, et al. AMON: a wearable multiparameter medical monitoring and alert system. Inf Tech Biomed, IEEE Trans on. 2004;8(4):415–427.
25. Pandian PS, Mohanavelu K, Safeer KP, et al. Smart Vest: Wearable multiparameter remote physiological monitoring system. Med Eng Phys. 2008;30(4):466–477.
26. Montgomery K, Mundt C, Thonier G, et al. Lifeguard—a personal physiological monitor for extreme environments. In: Engineering in Medicine and Biology Society: 26th Annual International Conference of the IEEE
, September 1–5; San Francisco, CA: National Center for Space Biological Technology, Stanford University; 2004:2192–2195.
28. Georgia Institute of Technology. Georgia tech wearable motherboard. http://www.gtwm.gatech.edu/
. Updated 2002. Accessed September 26, 2010.
29. 39th Design Automation Conference, DAC 2002, New Orleans, LA, USA, June 10–14, 2002. ACM 2002, ISBN 1-58113-461-4.
30. 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society “Merging Medical Humanism and Technology” August 31- September 4, 2010, Buenos Aires, Argentina.
31. 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society Minneapolis, Minnesota Sept 3-6-2009.
32. Marschollek M, Wolf K, Gietzelt M, Nemitz G, Meyer zu Schwabedissen H, Haux R. Assessing elderly persons' fall risk using spectral analysis on accelero-metric data—a clinical evaluation study. 2008:3682–3685.
33. Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–148.
34. Oliver D, Britton M, Seed P, Martin FC, Hopper AH. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: case-control and cohort studies. BMJ. 1997;315(7115):1049–1053.
35. Mahoney FI, Barthel DW. Functional evaluation: the Barthel index. Md State Med J. 1965;14:56–65.
36. Narayanan MR, Scalzi ME, Redmond SJ, Lord SR, Celler BG, Lovell NH. Evaluation of functional deficits and falls risk in the elderly—-methods for preventing falls. In: Proceedings of the 31st Annual International Conference of the IEEE EMBS, September2–6; Minneapolis, MN; 2009: 6179–6182.
37. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003;83(3):237–252.
38. Farberow B, Hatton V, Leenknecht C, Goldberg LR, Hornung CA, Reyes B. Caveat emptor: the need for evidence, regulation, and certification of home telehealth systems for the management of chronic conditions. Am J Med Qual. 2008;23(3):208–214.
39. Milhailidis A, Cockburn A, Longley C, Boger J. The acceptability of home monitoring technology among community-dwelling older adults and baby boomers. Asst Technol. 2008;20(1):1–12.
40. Mann W., OTR, PhD, Marchant T, MOTS, Tomita M, Fraas L, OTR, MA, Stanton K MS, RN. Elder Acceptance of Health Monitoring Devices in the Home. Care Management Journals. 2002;3(2):91.
41. Marschollek M, Wolf K, Plischke M, et al. People's perceptions and expectations of assistive health-enabling technologies: an empirical study in Germany. Assist Technol. 2009;21:86–93.
42. Courtney K, Demiris G, Rantz M, Skubic M. Needing smart home technologies: the perspectives of older adults in continuing care retirement communities. Inform Primary Care. 2008;16:195–201.
43. Courtney KL. Privacy and senior willingness to adopt smart home information technology in residential care facilities. Methods Inf Med. 2008;47:76–81.
44. Walivaara B, Andersson S, Axelsson K. Views on technology among people in need of health care at home. Int J Circumpolar Health. 2009;68(2):158–169.
45. Alwan M, Felder R, eds. Eldercare Technology for Clinical Practitioners. Totowa, NJ: Humana Press; 2008.
falls detection; monitoring; wearable technology