Palm carotene was successfully concentrated from crude palm oil by a single-stage chromatographic process on a synthetic porous polymer. Carotene was concentrated to about 10 5 ppm solution, which is about 160 times the original concentration in crude palm oil. Carotene recovery varied from 40 to 65% depending upon chromatographic conditions. The fatty acid composition of the palm oil did not change during the carotene recovery process, and the carotene composition was also almost the same as that in palm oil. Adsorption isotherms of the adsorbent differed from other adsorbents. This new recovery method for palm carotene may be suitable as an edible palm oil pretreatment process due to its efficient mass recovery of a valuable bioresource. JAOCS 75, 399-404 (1998).

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Background: Falls are a significant incident among older adults affecting one in every three individuals aged 65 and over. Fall risk increases with age and other factors, namely instability. Recent studies on the use of fall detection devices in the Malaysian community are scarce, despite the necessity to use them. Therefore, this study aimed to investigate the association between the prevalence of falls with instability. This study also presents a survey that explores older adults' perceptions and expectations toward fall detection devices.Methods: A cross-sectional survey was conducted involving 336 community-dwelling older adults aged 50 years and older; based on randomly selected participants. Data were analyzed using quantitative descriptive analysis. Chi-square test was conducted to investigate the associations between self-reported falls with instability, demographic and walking characteristics. Additionally, older adults' perceptions and expectations concerning the use of fall detection devices in their daily lives were explored.Results: The prevalence of falls was 28.9%, where one-quarter of older adults fell at least once in the past 6 months. Participants aged 70 years and older have a higher fall percentage than other groups. The prevalence of falls was significantly associated with instability, age, and walking characteristics. Around 70% of the participants reported having instability issues, of which over half of them fell at least once within 6 months. Almost 65% of the participants have a definite interest in using a fall detection device. Survey results revealed that the most expected features for a fall detection device include: user-friendly, followed by affordably priced, and accurate.Conclusions: The prevalence of falls in community-dwelling older adults is significantly associated with instability. Positive perceptions and informative expectations will be used to develop an enhanced fall detection incorporating balance monitoring system. Our findings demonstrate the need to extend the fall detection device features aiming for fall prevention intervention.

PurposeThe ever-increasing ageing population has raised awareness globally. The deterioration of health among older persons commonly leads to an increased risk of falling. The desire to live independently has the consequences for them and society as well. Enabling environments for older persons can be created, easing the social challenge of preparing for an ageing society while improving quality of life in their golden years. Technology solutions have been a game-changer supporting the families as the default caretakers for ageing relatives, bringing peace of mind. Fall detection systems represent one of the assistive technologies for older persons, as they can offer immediate assistance in case of emergency. Albeit the usage of the device is statistically low in Malaysia, they have been known to save lives (Bourke et al., 2010). Studies regarding fall detections and balance intervention have resulted in increasing safety, improving gait and physical activities (Lin & Wai, 2021;Hsieh et al., 2018). This study aims to improve the device by incorporating balance monitoring system, delivering better care for older persons. Rather than simply detecting falls, the proposed system will monitor balance instability, alerting the user to predict future falls and therefore serving as a fall prevention device. Method A simulation-based study has been developed to monitor balance instability of older persons. A fall prevention algorithm is proposed to be integrated with fall detection devices, where two notable variables of balance were selected as the inputs for the system: Limit of Stability (LOS) and Degree of Sway (DOS). Findings are validated using real data of older persons' LOS and DOS, adopted from a previous research by Ashari (2007) which used Neurocom™ Balance Master for balance analysis. The balance instability is then analysed using fuzzy logic and categorised as low, medium, or high; signified as the fall risk level (Figure 1). The classification will be displayed in the balance assessment while the system concurrently detecting fall events. Results and Discussion This study demonstrates a fall prevention algorithm to improve the accuracy of fall detection systems while monitoring balance instability. The system will notify the user if there are instabilities detected to avoid falling or prolonged loss of balance. When the simulation is initiated, the system will continuously monitor older person's stability while detecting falls. Results will display balance category with an indicator displaying fall risk level and notifications of actions to be taken for safety purposes. Figure 1 demonstrates the balance assessment of a user with low level of stability, thus the fall risk indicator level becomes high and necessary actions is taken immediately via the system. Analysing balance instability among older persons is an important aspect for their daily monitoring and to be aware of their conditions periodically. This will help health care professionals to provide proper rehabilitation if needed. The enhanced fall d...

Engineering invention must be in tandem with public demands. Often it is difficult to identify the priorities of consumers where technological advancement is needed. In line with the global challenge of increasing fall prevalence among older adults, providing prevention solutions is the key. This study aims at developing an improved fall detection device using an approach called Quality Function Deployment (QFD). The goal is to investigate features to incorporate in existing device from consumer’s perspectives. A three-phases design process is constructed; (1) Questionnaire, (2) Ishikawa Method, and (3) QFD. The proposed method begins with identifying customer needs as the requirement analysis, followed by a method to convert them to design specifications to be added in a fall detection device using QFD tool. As the top feature is monitoring balance, the new improved fall detection devices incorporating balance features will help older adults to monitor their level of risk of falling.